to teach pronunciation. We teach grammar, we teach reading, we teach writing, we teach listening, but, teaching pronunciation is not accentuated in the programs. (MK05)

When pronunciation is addressed in the classroom, it is rarely addressed separately, e.g., a whole lesson being devoted to explaining and practising pronunciation features (n = 5); it is typically integrated in the L2 lesson (n = 24). This is mostly done when new vocabulary is introduced (accurate pronunciation presented), when speaking is practised (mispronunciations corrected), when reading is practised (mispronunciations corrected), or when listening is practised (the focus being more on listening comprehension exercises in the coursebook than discriminating sounds in speech). Apparently, they do not systematically teach pronunciation and barely mention pronunciation aspects; the presentation of various pronunciation features is rather unplanned. Only a selection of features are taught, predominantly word stress, then vowels (long vs. short, /æ – e/), diphthongs, consonants (mainly /θ, ð, t, d/, i.e., consonants that are difficult for Macedonian learners of English), intonation patterns (e.g., in tag questions or the meaning of rising and/or falling tones), and the pronunciation of <-s> and <-ed>. Phonemic symbols and letter-to-sound connections are seldom taught, as well as syllable division. It was interesting to notice from their responses that they frequently used the term *understandable* to mean intelligible and/or comprehensible.

The type of pronunciation activities that are practised is varied. When the focus is on specific speech sounds, the activities are more controlled and include elicited imitation (listen and repeat), individual sound identification/categorisation, minimal pairs for sound discrimination, reading-aloud, dictation with phonemic symbols, and tongue twisters. When the aim is to make the lesson more interactive and fun, then communicative activities are practised, such as games, quizzes, and dialogues in the form of role-plays (not necessarily with a strong focus on pronunciation practice). One participant mentioned organising a debate club and mock trial courts (MK06), and another a drama studio (MK24) – these teachers use such activities to address pronunciation issues in context. Several teachers sometimes use activities from a coursebook (n = 13), few create materials or use other resources in addition to the coursebook activities (n = 7), and some do not even have coursebooks, as in some schools teachers are required to create their own materials and do not use coursebooks at all (n = 9). Those teachers who use coursebooks but do not practise pronunciation activities in the coursebook, reported that they do so because it is not required in the curriculum. Several teachers (n = 10) make use of resources that are incidentally found online and the online resources they select are chosen in relation to their learners' age, including short stories, songs, listening activities, interactive minimal pair activities, etc. Many teachers (n = 16) consult specific sites, for instance, Kahoot!<fnref n="3" />, online dictionaries, Live Worksheets<fnref n="4" />, slam poetry websites – to name a few. One teacher (MK23) reported that when she noticed that her learners struggled with a particular pronunciation aspect, she would consult specialised teacher development sites; it is important to point out here that this teacher enjoys institutional support in this respect (the institution covers the subscription cost but this is only the case in the private international schools). Three teachers reported not using online resources at all.

With respect to the ways they correct their learners' pronunciation, the responses were mixed. In general, the teachers use reformulations (predominantly explicit correction, occasionally recasts) and prompts for self-repair (mainly repetition). Corrective feedback is given mostly individually and immediately when the mistake is made. Some teachers prefer giving delayed feedback (they wait for the learners to finish the task and then they clarify the

<footnote n="3">³ Kahoot! https://kahoot.com/</footnote>

<footnote n="4">⁴ Life Worksheets https://www.liveworksheets.com/</footnote>
mispronunciation either to the learner who made the mistake or as a general correction in front of the whole group).

During the interviews teachers made unsolicited remarks: the majority reported forgetting core pronunciation knowledge (phonetic/phonological rules). With this weakness in mind, they observed that they would benefit from specialised courses for teaching pronunciation. Such incidental findings ring alarm bells about teachers' self-identified needs for systemic guidance and opportunities for continuing professional development.

These preliminary results reveal some of what actually goes on in classrooms and provide insight into an important aspect that has received little attention in research: genuinely understanding classroom reality – a reality that assumes increased workload, limited resources, and a lack of autonomy and self-confidence (see Figure 2). Such a constraining professional context inevitably leads to teachers being discouraged to engage in teaching pronunciation and who, in truth, need support to navigate the personal and institutional challenges. They also need to be encouraged to address pronunciation issues in their teaching more frequently.

<figure><img src="image_47.png" /><figcaption>**Figure 2**

*Professional Contextual Constraints Discouraging Teachers from Engaging to Teach Pronunciation*</figcaption></figure>

## 4 Discussion

The findings presented in this analysis at least hint that perhaps one way of addressing teachers' discouragement with regard to teaching pronunciation is to have researchers understand their harsh reality and make their research more accessible and comprehensive – research should empower teachers to develop a proactive approach to teaching pronunciation rather than a reactive one. The ideal teacher profile is a competent teacher who is trained to teach pronunciation and informed about the latest research evidence of what is effective. Equally important, teachers should be skilled and confident to make more spontaneous decisions in the
classroom. This is, of course, easier said than done, but it is in truth achievable. Instead of overwhelming teachers with a profusion of theoretical information, recommendations could be made on how to take small steps of action. For instance, it is paramount that teachers be equipped with a reasonable phonological know-how on which they can build their teaching practice. Table 1 shows initial recommendations on how a teacher who is assumed to know little about pronunciation teaching or feels discouraged about it might enhance their competence and classroom routines over time.

<caption>**Table 1**</caption>

*Approaching Pronunciation Teaching in the Classroom*

<table><thead><tr><td>Having the know-how</td><td>Noticing the problem</td><td>Addressing the problem</td></tr></thead><tbody><tr><td><ul><li>Inform yourself about the L2 sound system.</li><li>Do a diagnostic assessment of your students' speech.</li></ul></td><td><ul><li>Observe your classroom context and start with one pronunciation activity (research-grounded).</li><li>See what works best for your students and build on that experience.</li></ul></td><td><ul><li>Foster intelligible pronunciation for communication.</li><li>Encourage autonomous learning and use of online resources.</li></ul></td></tr></tbody></table>

It is important to highlight that providing support, collaborating, and partnering are key elements for nurturing a successful approach to pronunciation teaching.

In terms of the circulation of information, new knowledge needs to be regularly disseminated and shared through various fora and publications. A perfect example of a successful connection between research and practice are teachers' associations. In particular, the following deserve a special mention: the IATEFL Pronunciation Special Interest Group (PronSIG), the TESOL Speech Pronunciation Listening Interest Section (SPLIS), and the CATESOL Teaching of Pronunciation Interest group (TOP-IG).<fnref n="5" /> These associations boast a community of enthusiasts who are active researchers and practitioners and who regularly organise conferences and online webinars (both theoretical and practical), share professional development content, publish their own journals<fnref n="6" />, as well as share pronunciation-related teaching tips via podcasts, blogs, and social media reels. Furthermore, other good practices are promoted via various platforms where resources for teachers and learners are available such as (among others): English Accent Coach<fnref n="7" /> for practising L2 perception through HVPT exercises; task banks, e.g., TBLT Language Learning Task Bank<fnref n="8" />; SLA Speech Tools<fnref n="9" /> website, which

<footnote n="5">⁵ IATEFL Pronunciation Special Interest Group – PronSIG https://pronsig.iatefl.org/
TESOL Speech Pronunciation Listening Interest Section – SPLIS https://www.tesol.org/
CATESOL TOP-IG: Teaching of Pronunciation Interest group https://www.catesol.org/</footnote>

<footnote n="6">⁶ Speak Out! https://pronsig.iatefl.org/journal/
TESOL Quarterly https://onlinelibrary.wiley.com/journal/15457249)
The CATESOL Journal http://www.catesoljournal.org/</footnote>

<footnote n="7">⁷ https://www.englishaccentcoach.com/</footnote>

<footnote n="8">⁸ https://tblt.indiana.edu/tasks/details.html?id=73</footnote>

<footnote n="9">⁹ http://sla-speech-tools.com/</footnote>
offers a variety of tools for research and teaching; PhoTransEdit<fnref n="10" /> application for practising
phonemic transcription, etc. Recently, publications with a specific focus on enhancing
teachers’ pronunciation knowledge – Liu et al. (2023) being a notable example – have captured
publishers’ attention. Practically-oriented publications with detailed descriptions of courses
with an integrated pronunciation component (Murphy, 2017) have also been available on the
market. These are examples of already successful practices that should continue to be
encouraged.

These achievements – in creating communities and resources – could be combined in an all-inclusive multi-content platform that would serve as a reference point for researchers, teachers, and learners. Such a platform – call it a Pronunciation Core – could serve as a medium for teaching and learning English pronunciation. It would aim to provide professional help to English language teachers by joining the two worlds of research and practice and narrowing the existing gap, where ideas and practical suggestions based on research findings could be offered, thus assisting teachers in making research-informed decisions and improving their teaching practices. These recommendations could be written in non-technical, simple language so that they address pre-service and in-service teachers’ immediate needs. The platform would be an ideal spot where various points of interests could intersect: a) concepts explained; b) research updates and practical implications shared; c) useful links and resources for the classroom linked; d) typical features of diverse native and non-native accents described; e) professional development instructional videos uploaded; f) social media networks built; etc.

Finally, one aspect that begs for urgent action is opening a conversation between researchers
and teachers, on the one hand, and coursework developers on the other. It is crucial that
pronunciation as a language skill is given equal treatment in published teaching materials. After
all, pronunciation should not be treated as an optional element in the classroom – it needs to be
part of every lesson so that teachers can accommodate to their learners’ needs.

5 Conclusion

This chapter examines aspects of the on-going debate on how to link pronunciation research and practice. It evaluates effective research findings related to important pronunciation issues, which pedagogy needs to take into consideration. It also considers their implications in the L2 classroom, especially from teachers’ point of view, and discusses the challenges they face in their professional lives. In doing so, the paper has a two-fold aim: to invite researchers to reflect on how they see pedagogy and to redefine how teachers approach research.

Future endeavours will reveal whether value-added relations are developed between these
two communities, who do not always have overlapping roles. Just as much as teachers need
support, in the form of highlighted research results and their incorporation into hands-on
materials, researchers also need directions from teachers as to which pedagogical issues are
more pressing and should be brought to their attention. Undoubtedly, more research should be
focused on innovation and practical application in designing actual output resources that can
be applied in the classroom. In addition, teachers should reflect on their teaching practice and
context in light of current research findings, so that they can inform themselves, build on their
existing knowledge, and strengthen their confidence to teach pronunciation. Such an approach
is useful in the long run and will empower teachers to make more spontaneous decisions in the
classroom about what and how to teach. In this way, they will be better able to help their
learners reach their goals. By bringing in a reasonable amount of structure, and affording
teachers enough opportunities for autonomous action, feelings of discouragement about

<footnote n="10">¹⁰ http://www.photransedit.com/</footnote>
teaching pronunciation could be minimised and better practices could be promoted and
developed.

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## About the author

Anastazija Kirkova-Naskova is an Associate Professor in English phonetics and morphology in the Department of English Language and Literature, Ss. Cyril and Methodius University in Skopje, North Macedonia. She also teaches research methodology (MA level). Her research interests include English pronunciation teaching and learning, foreign-accented speech, speech perception, pronunciation learning strategies, and teacher cognition. Together with Alice Henderson and Jonás Fouz-González, she co-edited *English pronunciation instruction: Research-based insights* (John Benjamins, 2021). She was an assistant editor-in-chief for *The Journal of Contemporary Philology*.

Email: akirkova@flf.ukim.edu.mk
Kivistö de Souza, H. & Lintunen, P. (2023). “Thinking about your pronunciation”: Examining phonological self-awareness with a novel task. In A. Henderson & A. Kirkova-Naskova (Eds.), *Proceedings of the 7th International Conference on English Pronunciation: Issues and Practices* (pp. 138–148). Université Grenoble-Alpes. https://doi.org/10.5281/zenodo.8225603

“Thinking about your pronunciation”: Examining phonological self-awareness with a novel task

Hanna Kivistö de Souza

Federal University of Santa Catarina, Florianópolis and University of Turku

Pekka Lintunen

University of Turku

Noticing the gap in one's pronunciation is notoriously demanding (Piske, 2008), and yet becoming aware of pronunciation challenges is beneficial for overall pronunciation competence (Kivistö de Souza, 2017). Previous studies on phonological self-awareness have employed global tasks such as journaling (e.g., Kennedy & Blanchet, 2014), and have pointed out that more explicit learning conditions lead to more noticing (White & Ranta, 2002). The objective of this paper is to present an instrument that examines second language phonological awareness by bringing the phonetic detail explicitly into the learners' attention. The participants were 33 L1 Finnish advanced university learners of English attending an undergraduate course on English phonetics and phonology. At the beginning of the semester, the participants provided a speech sample targeting tricky English sounds. At the end of the semester, a “Thinking about your pronunciation” task was administered in which the samples were played back to the participants. They were asked to indicate any pronunciation deviations they could perceive and to elaborate on how they perceived their own intelligibility and their abilities in recognising phonetic and phonological phenomena in their own and others’ speech. Our observations with the task indicate that the instrument can be a helpful and reliable tool in tapping into phonological self-awareness.

**Keywords:** phonological awareness, phonological self-awareness, pronunciation instruction, noticing, language awareness

<figure><img src="image_48.png" /></figure>

This chapter is based on the oral presentation given by the authors at the 7th International Conference on English Pronunciation: Issues and Practices (EPIP 7) held May 18–20, 2022 at Université Grenoble-Alpes, France. It is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of the license, please go to: http://creativecommons.org/licenses/by/4.0/.
# 1 Introduction: Research on phonological self-awareness

Language users possess vast amounts of knowledge about the phonological systems of the languages they speak, known as phonological awareness, as evidenced by accurate production and perception of target language sounds, syllables, stress, and intonational patterns. Furthermore, they are able to recognise phonological deviations in the form of a foreign accent, even when the speech sample is extremely short and played backwards (Munro, Derwing & Burgess 2003). Adult language users' phonological awareness thus entails knowledge about the target language phonological system at the subphonemic, segmental, and suprasegmental levels.

Phonological awareness also involves knowledge about one's own phonological competence (Kivistö de Souza, 2015), and includes noticing the gap (Schmidt & Frota, 1986) between one's own production and the target production. Such awareness is also evidenced by language users' ability not only to recognise foreign accented speech but also to provide accuracy judgments on others' speech. Noticing the gap has also been referred to as phonological self-awareness (Kivistö de Souza, 2015) or as phonological self-assessment or self-perception (Isbell & Lee, 2022; O'Brien, 2019). Nevertheless, noticing (i.e., becoming aware of a specific stimulus) does not necessarily entail understanding (i.e., verbalisation of the underlying rules), as these are seen as two distinct levels of language awareness (Schmidt, 1990).

Previous research on phonological self-awareness indicates that speakers' assessment of their pronunciation abilities correlates moderately with the actual performance (e.g., Saito et al., 2020; Trofimovich et al., 2016). However, speakers often tend to either over- or underestimate their pronunciation skills rather than to provide accurate self-assessments. Language learners whose phonological self-awareness is accurate have been shown to have more accurate segmental (e.g., Saito, 2019) and suprasegmental (e.g., O'Brien, 2019) pronunciation. Noticing phonetic detail in regular classroom interactions can be challenging, and research suggests that drawing learners' attention to phonetic detail and explicitly focusing on L2 pronunciation features is beneficial for L2 pronunciation development (Saito, 2021).

Many of the previous studies about L2 phonological awareness have presented the participants with global tasks such as free journaling (Kennedy & Blanchet, 2014; Kennedy & Trofimovich, 2010), stimulated recall (Wrembel, 2011, 2013) or imitating L2 accented speech (Mora, Rochdi & Kivistö-de Souza, 2014). The objective of the present study was to develop an instrument that would bring phonetic detail into the learners' attention in a more focused and controlled manner by prompting learners to engage in in-depth reflection about their pronunciation.

# 2 Methodology

## 2.1 Thinking about your pronunciation: Task format

An instrument we called a “Thinking about your pronunciation” task was created to examine the phonological self-awareness of advanced English speakers taking a course in English phonetics and phonology. The objective of this task was to encourage the students to engage in self-reflection in relation to their English pronunciation. The task was carried out towards the end of the semester and thus also served as an opportunity to revisit the course contents. Our previous experience with similar tasks suggested that students would have difficulties in noticing phonological challenges in their own pronunciation (Lintunen, 2013). For this reason, we tried to design a task consisting of four parts (see Appendix) that would be as explicit as possible and would offer ample opportunities for noticing.
In Part 1, the participants listened to a speech sample they had provided at the beginning of the semester and indicated any pronunciation deviations they could notice. The speech sample was a wordlist recording of 12 words containing phonemes and features known to be challenging for L1 Finnish speakers of English (e.g., Lintunen, 2004), namely: aspiration, voiced plosives in word initial and final position as well as reinterpretation of distinctions in vowel contrasts. All the target items were high frequency monosyllabic CVC words. When recording the speech sample, the participants were not aware of the target sounds nor that they would analyse the pronunciation later in the semester. To increase noticing, each word was played three times, and with each time, the participant was asked to focus on one target sound (the initial consonant, the vowel or the final consonant). The participants were asked to mark whether they had pronounced the target sound correctly or not. Optionally, they could also explain why they thought their pronunciation was inaccurate. We chose to use the term 'correct' to describe phonologically accurate, non-deviant productions to facilitate the participants' comprehension. The definition of 'correct' was not given in the instructions, but we assumed that the participants' perceptions of correctness would adhere to a nativeness norm and vary from native production to near-native-like.

Once the participants had focused on each segment in each of the 12 target words separately, they were asked in Part 2 to indicate if they thought that certain words were entirely unintelligible for other English speakers. The objective of Part 2 was to allow the participants to elaborate in more detail on the items they considered especially challenging.

Part 3 consisted of the participants' self-assessment of their overall English pronunciation. They were asked to indicate on a 7-point Likert scale how comprehensible they thought their speech is for native English speakers. This question aimed to guide the participants' attention to their pronunciation as a whole, in comparison to focusing on specific pronunciation instances as in the first two sections. Moreover, whereas Part 1 focused on perceptions of accuracy (i.e., how much the pronunciation deviates from the target) and Part 2 on the perception of intelligibility (i.e., how well the productions are understood by other English speakers), Part 3 focused on self-perceived comprehensibility (i.e., how much effort the listener needs to understand the speech) (Munro & Derwing, 1995).

The final section, Part 4, was adapted from Kivistö de Souza (2015), and it focused on the participants' self-assessment of their phonological abilities. The section consisted of a set of phonological self-awareness questions the participants were asked to provide their opinion on. These questions asked, for instance, how easy it was for them to: notice pronunciation mistakes in other non-native English speakers' and their own speech, identify English spoken with different accents and explain mistakes of phonological nature. The objective of Part 4 was to explore the participants' self-reports on the two levels of language awareness, i.e., noticing and understanding (Schmidt, 1990).

## 2.2 Participants and raters

The participants were 33 L1 Finnish speakers doing an undergraduate degree in English language. Their mean age was 21.2 years, and their English proficiency was estimated to correspond to CEFR level C1, as indicated by their LexTALE scores (M = 86.70, SD = 7.35) (Lemhöfer & Broersma, 2012, p. 341). Twelve participants were male, 18 female and three did not disclose gender information. At the time of data collection, the participants were enrolled in an obligatory first-year practical course on English phonetics and phonology which aimed at improving students' pronunciation through practical exercises, as well as description and transcription of English phonemes. The raters were three university professors specialising in English Phonetics and Phonology with extensive experience in rating speech samples. Two raters were L1 Finnish speakers and one rater was an L1 Portuguese speaker.
## 2.3 Procedures and analyses

The speech samples (word list readings) for the first part of the task were recorded at the beginning of the semester as part of a larger project. First, the recordings' sound quality was improved by removing noise and normalising the speech samples with Audacity© (Audacity Team, 2021). Then, for each of the 33 participants individual recordings were created in Praat (Boersma & Weenik, 2022). The target words were isolated from a larger set of stimuli and combined into a new sound file together with silent pauses. Each word was copied into the file three times with a one second pause between the words. The final repetition of the word was followed by a three second pause to indicate the change of a set. The recordings were approximately 2.5 minutes long.

The recordings and the instructions were made available through the course's virtual learning platform Moodle, to which the researchers were granted access by the course instructors. Additionally, printed copies of the answer sheets were handed out to the participants in class. Each participant had access to their own recording only. The participants completed the self-paced task at home as an additional non-graded homework assignment. The instructions were given to carry out the task in a calm environment with headphones, if available. Repeated listening of the recordings was allowed. Once the participants had completed the entire task, they submitted the answer sheets through Moodle. Instances of noticing of pronunciation deviations (instances marked as 'inaccurate' in the answer sheet) were computed for each participant and target feature, and then converted into percentages.

To determine whether the participants were noticing actual pronunciation deviations or indicating deviations in accurate productions (i.e., being overly critical), the participants' scores were compared to performance rating scores given by three expert raters. Two raters assessed all samples for accuracy and their overall agreement was 85.7%. When agreement could not be reached, the samples were additionally assessed by a third rater.

## 3 Results

This section describes our observations on the use of the instrument. (For detailed results see Kivistö de Souza and Lintunen (forthcoming)).

Very few data were missing from Part 1 (11 out of 1188 instances = 0.01%) in which participants listened to their speech samples and assessed their correctness, suggesting that they understood the task and put some effort into completing it, despite not being in the presence of a researcher. Participants differed greatly in their self-assessments and reported noticing on average 9.12% (range: 0–30%) of the pronunciation deviations (i.e., indicated as ‘not correct’ on the answer sheet). Most of the deviations noticed were in initial consonants (M = 12.13%, range: 0–62%), followed by final consonants (M = 7.81%, range: 0–34%) and vowels (M = 7.41%, range: 0–33%). Among the phonetic phenomena analysed (aspiration, voiced stops, vowel quality), the most frequent problems were in pronouncing initial voiceless plosives (inadequate VOTs; 14.7%, range: 0–100%). Deviations in voiced stops (devoicing) were slightly less frequent (M = 10.58%, range: 0–40%).

When the participants' reported noticing is compared with their actual performance, a slightly different image appears. By looking at the raters' assessments of the participants' pronunciation accuracy and comparing them with the participants' reported noticing, the participants' overall pronunciation accuracy was very high (M = 97.90%, range: 37.5–100%), and the participants noticed on average 25.9% of the pronunciation deviations present. However, the range of noticing varied from 0 to 100%, indicating a large individual variation in participants' phonological self-awareness.
On very few occasions, the participants (P) chose to elaborate on the deviations they had noticed (93 out of 1188 instances = 0.07%), most likely because this was presented as an optional activity. Short comments were more frequently used, for instance: “not clear enough” (P28), “too Finnish” (P57), “not aspirated” (P73). Longer and more detailed comments were also present in the data though less frequently, for example: “I emphasise the sound too much in order to not make it sound like the consonant "p", which makes it sounds weird” (P80).

Examining the responses to Part 2 where the participants could elaborate on specific items they considered unintelligible, three participants did not answer the question (10%), nine (27%) reported that they did not think any of their productions would be unintelligible, and the remaining 21 (63%) identified at least one word they considered to be unintelligible. The word that was mentioned as unintelligible most frequently (n = 9) was *pub*, followed by *buck* (n = 5). Both were reported to be easily mistaken for *pup* and *puck*, hence, the participants most likely perceived problems in consonant voicing. One participant commented that it would be difficult to know how other speakers would perceive their pronunciation.

In Part 3 where the participants rated their self-perceived comprehensibility, there was no missing data. The participants favoured the upper range of the scale (M = 5.6, range: 4–7), indicating that they did not expect native English speakers to experience problems in understanding them. This self-perception seems accurate as participants had a high English proficiency and were rated as highly accurate by expert raters.

The reliability of the set of phonological self-awareness questions was examined in section four. An earlier version of these questions was found to be an acceptable measure (n = 71, α = .75) for phonological self-awareness for Brazilian Portuguese learners of English (Kivistö de Souza, 2015). In the version used in the present study, Cronbach's Alpha of .84 indicated that the items had a relatively high internal consistency and thus could be seen to tap into the same underlying construct (phonological self-awareness). There were three missing data points (out of a total of 396 instances) indicating that even though the participants might have considered some of the questions difficult, they still tried to answer.

Looking at the individual questions that made up the scale, the participants as a group reported the highest ability in recognising Finnish-accented English (quite easy M = 4.3) as well as noticing pronunciation mistakes in their own pronunciation (quite easy M = 4.1). The lowest ability was reported in explaining why a heard sound combination is possible or impossible in English (very difficult M = 2.6) and why the heard intonation and rhythm patterns are correct or incorrect (very difficult M = 2.7).

# 4 Discussion and conclusions

Phonological awareness has been shown to be positively related to pronunciation accuracy (e.g., O'Brien, 2019; Saito, 2019), and consequently, methods and instruments to increase language learners' phonological awareness are highly relevant for L2 classrooms. In this paper we have described one such instrument that could be useful in drawing learners' attention to their L2 pronunciation. We tested the instrument with 33 advanced Finnish learners of English who were attending a course in English phonetics and phonology. Our objective was to create an instrument that would reliably tap into phonological self-awareness and encourage students to engage in self-reflection about their L2 pronunciation in a practical manner. Our preliminary observations suggest that the instrument can be useful in examining language learners' phonological self-awareness. Nevertheless, some issues arose from Part 1 of the instrument which researchers should address if they are interested in employing the tool.

We were aware that noticing the gap might be challenging, even for advanced language learners, which is why we tried to make Part 1 as explicit as possible. The participants received explicit instructions about which aspects to focus on and the task was self-paced, so the sound
files could be played several times. The words were all carefully selected to be monosyllabic and known to the learners, and they were presented in a controlled order in which minimal pair words followed each other (e.g., *pub* was followed by *pup*). This methodology contrasts with think-aloud protocols (Wrembel, 2013, 2015; Zuengler, 1988) and journaling (Kennedy, 2012; Kennedy & Blanchet, 2014; Kennedy & Trofimovich, 2010) which have been used previously to examine phonological awareness, as these methods allow for a wider attentional focus. Despite these efforts, the participants seemed to have a hard time identifying their segmental deviations, as testified by an average of 25.9% of noticed deviations, even though the participants possessed great amounts of metaphonological knowledge due to the course they were attending. Unsurprisingly, the participants found the syllabic and suprasegmental features difficult to explain, as the course they were attending was more focused on segmental phonology and had less emphasis on developing metalinguistic knowledge about English suprasegmentals.

Another possible reason for the low degree of noticing could be the participants' advanced proficiency level: when the production is accurate, there are fewer deviations to notice. However, phonological awareness is positively related to language proficiency (Kivistö de Souza, 2015), so the issue might not be as straightforward. It would be interesting to test participants with intermediate proficiency levels to determine how much noticing takes place.

Another possible reason for the participants' lack of noticing might be the task structure: as the task was carried out at home without researcher's supervision, the participants might have gotten distracted and might not have paid as much attention to the speech samples as they could have. However, as each participant received a different speech sample, working in a language lab was not a possibility for us.

A serious concern for researchers working with phonological self-awareness in this manner is the time required to create and administer the task. First, the researchers have to record the participants, create individualised sound files for each and finally individually send them through a cloud service or learning platform, for example. Second, when learners are asked to notice deviations in their own speech, the researchers have to make sure that those deviations are actually present in the speech samples. This requires either acoustic analysis or perceptual assessment. In the present study, we opted for the perceptual assessment of three teachers, but we are aware that ideally the speech samples should be presented to a larger number of raters.

A point should also be made about what is being noticed. Although we treat segments separately, speech is continuous and segments are affected by their surrounding context and speech rate, among others. When analysing the accuracy of the participants' productions, we had the specific difficulty of deciding, for instance, whether final inaccurate devoicing should be understood as a problem in the preceding vowel (that was too short) or in the lack of voicing of the consonant. These are issues that the researchers have to discuss in advance and while coding the data, in order to maintain consistency.

Finally, we would like to make a recommendation about combined measures of phonological self-awareness. Verbalising language awareness is difficult and verbalising phonological awareness appears to be even more so (Kivistö de Souza, 2015, p. 105; Schmidt, 1990, p. 132). It might be a good idea to complement tasks tapping into explicit phonological awareness, like the present one, with tasks that tap into non-verbalisable phonological self-awareness (e.g., perception, imitation, non-word recognition) for a comprehensive picture of the learners' phonological self-awareness (see Kivistö de Souza & Lintunen, forthcoming).

To conclude, despite the limitations, this instrument is a useful tool that can be used to address the complex aspects of phonological awareness, and it may help shed more light on how language users perceive their own pronunciation.
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# Appendix

## Thinking About Your Pronunciation Answering Sheet

### Instructions in a nutshell:

1. Download your recording from Moodle ("Thinking about your pronunciation homework")

<figure><img src="image_49.png" /></figure>

2. Make sure that you are in a quiet place where you can concentrate. If you have headphones, please use them.

3. Keep this answering sheet and a pen ready and play the recording. You will hear each word three times and each time you should pay attention to different parts of the word.

<figure><img src="image_50.png" /></figure>

4. Listen carefully and tick the answer that applies. If you're unsure, you can listen to the word again. You can also stop the recording to have more time to answer.

5. Once you have listened to all words, answer the questions at the end.

<figure><img src="image_51.png" /></figure>

6. Return the answering sheet to your teacher on the class 16th November. Alternatively, you can take pictures or scan your answers and upload them on Moodle.

<figure><img src="image_52.png" /></figure>

**Part 1. Did you pronounce the indicated part of the word correctly? If you didn't, you can explain shortly why.**

*There is a longer pause and a beep before the next word is presented. If you need more time before the next word, pause the recording when you hear the beep.*

### 1. Pup

<table><tr><td>The initial consonant <b>pup</b></td><td><input type="checkbox"/></td><td>Yes</td><td><input type="checkbox"/></td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>pup</b></td><td><input type="checkbox"/></td><td>Yes</td><td><input type="checkbox"/></td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>pup</b></td><td><input type="checkbox"/></td><td>Yes</td><td><input type="checkbox"/></td><td>No</td><td>(Why not?)</td></tr></table>

### 2. Pub

<table><tr><td>The initial consonant <b>pub</b></td><td><input type="checkbox"/></td><td>Yes</td><td><input type="checkbox"/></td><td>No</td><td>(Why not?)</td></tr></table>
<table><tr><td>The vowel <b>pub</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>pub</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 3. Bet

<table><tr><td>The initial consonant <b>bet</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>bet</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>bet</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 4. Bed

<table><tr><td>The initial consonant <b>bed</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>bed</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>bed</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 5. Buck

<table><tr><td>The initial consonant <b>buck</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>buck</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>buck</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 6. Bug

<table><tr><td>The initial consonant <b>bug</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>bug</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>bug</b></td><td>☐</td><td>Yes</td><td>☐</td><td>N</td><td>(Why not?)</td></tr></table>

### 7. Deed

<table><tr><td>The initial consonant <b>deed</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>deed</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>deed</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 8. Did

<table><tr><td>The initial consonant <b>did</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>did</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>did</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 9. Beat

<table><tr><td>The initial consonant <b>beat</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>beat</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>beat</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 10. Bit

<table><tr><td>The initial consonant <b>bit</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>bit</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>bit</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 11. Peak

<table><tr><td>The initial consonant <b>peak</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>peak</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>peak</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>

### 12. Pick

<table><tr><td>The initial consonant <b>pick</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The vowel <b>pick</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr><tr><td>The final consonant <b>pick</b></td><td>☐</td><td>Yes</td><td>☐</td><td>No</td><td>(Why not?)</td></tr></table>
**Part 2. Do you think that there is any word that you pronounced that might not be understood by other speakers of English (native or non-native)? Which one(s)?**

**Part 3. How easy do you think it is for native speakers of English to understand your pronunciation when you speak in English? Circle the corresponding number on the scale.**

<figure><img src="image_53.png" /></figure>

**Part 4. How easy it is for you to...**

*Write X on the corresponding box.*

<table><thead><tr><th></th><th>5<br>Very<br>easy</th><th>4<br>Quite<br>easy</th><th>3<br>Quite<br>difficult</th><th>2<br>Very<br>difficult</th><th>1<br>I can't<br>do this<br>at all</th></tr></thead><tbody><tr><td>notice pronunciation mistakes in the production of individual sounds in other non-native English speakers' speech?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>notice pronunciation mistakes in intonation and rhythm in other non-native English speakers' speech?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>notice pronunciation mistakes in your own English speech?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tell where a native speaker of English comes from based on their accent?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tell whether a non-native speaker of English is Finnish based on their English accent?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tell where a non-native speaker of English (not Finnish) comes from based on their English accent?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>notice whether a sound combination you hear is possible in English or not?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>notice whether the intonation and rhythm you hear in an English sentence are possible or not?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>notice whether an individual sound you hear is pronounced correctly in English or not?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>explain why a sound combination you hear is possible or impossible in English?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>explain why the intonation and rhythm you hear are correct or incorrect in English?</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>explain why an individual sound you hear isn't pronounced correctly in English?</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## About the authors

**Hanna Kivistö de Souza** is an Associate Professor at the Federal University of Santa Catarina (UFSC) in Brazil where she teaches and advises at the undergraduate and graduate levels. Her main research interests are L2 speech acquisition and cognitive- and psycholinguistics applied to SLA. She is especially fascinated by the role of phonological (self)awareness in L2 speech acquisition and has conducted research mostly on explicit and implicit phonological awareness as well as phonological self-awareness. In 2021, she was a visiting researcher at the University of Turku.

Email: hanna.kivistodesouza@gmail.com

**Pekka Lintunen** is a Professor of English at the University of Turku, Finland, where he heads the Second Language Acquisition track. Lintunen's main research field is the development of spoken L2 skills. Recently, his research has focused on the fluency and complexity of learner language, the learning and teaching of L2 pronunciation, learner perceptions and beliefs and informal language learning. Currently, he coordinates research projects for his FlowLang research group. Lintunen has also co-edited several publications, including *Fluency in L2 Learning and Use* (Multilingual Matters, 2020).

Email: pekka.lintunen@utu.fi
# English-medium-instruction lectures: Tackling the issue of (dis)fluency and accuracy measures

Xavier Martin-Rubió
University of Lleida

More and more higher education institutions require certification of language proficiency in order to teach content in English, but countries assess proficiency differently. Moreover, fluency and pronunciation accuracy are just two aspects in determining proficiency.

A group of researchers from five European universities collected data from interviews and classroom recordings of six lecturers per university in 2018-2019, to compare the realities of English Medium Instruction in these contexts and, later, to improve training for EMI lecturers. A sub-group of researchers conducted a CEFR classification of the 30 lecturers. Another sub-group carried out a (dis)fluency analysis of two, 3-minute monologic stretches of 10 lectures, from 2 different lecturers in each country. To measure fluency, Mean Syllables per Run, Rate of Speech Time and Time Ratios were considered, while for disfluency the number of repetitions and false-starts/self-corrections per 100 syllables was determined.

This chapter reflects upon the complexity that surrounds the concept of pronunciation accuracy by narrowing in on a specific case: one Italian lecturer's use of epenthetic vowels after final consonants. This case triggered a lengthy discussion among the researchers as to whether this was a pronunciation error, a feature of an Italian accent, or a filled pause. Assessing lecturers' proficiency is revealed as a complex process which is subject to broader norms.

**Keywords:** EMI, fluency, pronunciation accuracy, accent, higher education

<figure><img src="image_54.png" /></figure>
# 1 Introduction

English Medium Instruction is defined by Macaro (2018) as “the use of the English language to teach academic subjects (other than English itself) in countries or jurisdictions where the first language of the majority of the population is not English” (p. 19). Normally coupled with the idea of internationalisation, this phenomenon has been gaining ground across European universities. Wächter and Maiworm (2014) differentiated six regions within Europe and argued that there is a north-south divide when it comes to the number of English-Taught programs. According to the authors, the Nordic and Central-West regions have the highest number of such programs, even though recent increases are below the average because they have a high percentage of existing programs in English (e.g., 30% in the Netherlands and 38% in Denmark). Conversely, the South-West and South-East regions have seen impressive growth rates, although the overall numbers are still low (1.2% for Croatia, 2.3% in Spain, and 2.9% in Italy).

A group of researchers from five European universities received an Erasmus+ grant in order to compare the EMI realities in their five countries, to determine whether this north-south divide was confirmed, and to develop tools for improving EMI lectures. These countries cover four of the six regions identified by Wächter and Maiworm (2014): Denmark represents the Nordic region, the Netherlands the Central-West, Spain and Italy represent the South-West, and the South-East is represented by Croatia. The project, entitled "Transnational Alignment of English Competences for University Lectures" (TAEC henceforth), ran from September 2017 to April 2021.

# 2 The TAEC project: Sub-groups and actions

There were seven transnational meetings in TAEC, and the objective to collect data was adopted at the first one held in Copenhagen, October 2017. The TAEC research group consisted of researchers from the following universities: University of Copenhagen, in Denmark (UCPH), Universitat de Lleida, in Spain (UdL), Maastricht University, in the Netherlands (UM), Università degli Studi di Torino, in Italy (UNITO) and the Faculty of Humanities and Social Sciences of the University of Rijeka, in Croatia (FHSS). Six EMI lectures were collected and six interviews were conducted per university. Table 1 provides a visual summary of the sub-groups and their actions.

<caption>**Table 1**</caption>

*TAEC Project Sub-groups and Actions*

<table><thead><tr><td>Sub-group</td><td>Members</td><td>Actions</td></tr></thead><tbody><tr><td>A</td><td>6 TOEPAS experts<br>6 CEFR experts</td><td><ul><li aligning TOEPAS (test used in UCPH) with CEFR</li></ul></td></tr><tr><td>B</td><td>8 raters<br>(TAEC members)</td><td><ul><li>rating 10–15 minutes of the 30 lectures using the CEFR scale</li><li>calculating (dis)fluency measures of two, 3-minute stretches for 10 of the lectures</li><li>identifying mismatches between CEFR ratings and measures</li></ul></td></tr><tr><td>C</td><td>2 TAEC members</td><td><ul><li>setting-up of transcription guidelines and corpus annotation criteria</li></ul></td></tr><tr><td>D</td><td>7 TAEC members</td><td><ul><li>identifying mismatches between CEFR ratings and measures</li></ul></td></tr></tbody></table>
<table><thead><tr><th>Sub-group</th><th>Members</th><th>Actions</th></tr></thead><tbody><tr><td>E</td><td>all members</td><td><ul><li>organising the revision of the transcriptions</li><li>transcribing and revising the transcriptions of the lectures</li><li>deciding how to annotate (mis)pronunciations</li><li>deciding whether an epenthetic vowel constitutes a filled pause rather than an error</li></ul></td></tr></tbody></table>

In the third meeting (Maastricht, May 2018), it was agreed that each university would audio and video-record six lectures by six different lecturers from different disciplines and academic levels, and that the lectures would be transcribed. The lecturers were also to be interviewed. Thus, a total of 30 interviews and 30 lectures would be gathered altogether. It was also agreed that insights from the analyses of the videos would be used to create a handbook that could then be used to train EMI lecturers.

The research team was organised into different overlapping sub-groups. One of them was in charge of rating the English level of the lecturers. Eight raters were asked to pay attention to eight aspects of oral production and to provide a holistic assessment as well. Each rater was asked to rate the videos independently, without discussing the results with other raters and/or colleagues. Ten to 15 minutes of each lecture that included both monologue and (when possible) interaction were to be selected by each evaluator. A small sub-group of just two researchers carried out a (dis)fluency analysis of two, 3-minute monologic stretches of 10 lectures, from 2 different lectures in each country. The chosen fluency measures were: Mean Syllables per Run; Rate of Speech Time; and Time Ratios. For disfluency, the number of repetitions and false-starts/self-corrections per 100 syllables was determined. Finally, another sub-group of seven members managed the transcription of the lectures, tagging grammatical and pronunciation errors in the transcription. Initially, this was done with the intention of calculating (pronunciation) accuracy measures of the lecturers, but the validation process for the transcriptions revealed great discrepancies in relation to what constituted an error, so the transcriptions were finally cleared of these tags.

## 3 Lecturer proficiency levels: TOEPAS and TAEC ratings

A content lecturer in higher education needs an adequate level of the language of instruction to effectively implement the different tasks they must carry out. However, what this adequate level should be remains a controversial matter.

In the last two decades, a number of tests have appeared, specifically to address this issue in relation to EMI lecturers. The Test of Oral English Proficiency for Academic Staff<fnref n="1" /> (TOEPAS henceforth) is the test used by the Center for Internationalisation and Parallel Language Use, University of Copenhagen. TOEPAS only focuses on oral production. The test, which is taken by three lecturers in a single session, is structured into three sections: a warm-up section, a 20-minute lecture simulation, and a final part for questions. As part of TAEC (see above), the TOEPAS test was aligned to CEFR. The alignment took place over a three-day standardisation event in October 2018 (see Dimova, 2018). There were 12 participants in the event, six of whom were familiar with TOEPAS, whereas the other six had expertise in rating using the CEFR (Council of Europe, 2018) scale.

The TOEPAS is a performance-based speaking test, and the maximum number of points is 60. A 30-point rating corresponds to a pass: "the lecturer has demonstrated sufficient English

<footnote n="1">¹ https://cip.ku.dk/english/documents/TOEPAS_2.0_A4_final.pdf</footnote>
Although the amount of changes and additions did not go over the minimum standards established, it was finally agreed to remove the tags from the transcriptions.

In relation to the rating of the lecturers, it was stated in the instructions that each rater would rate all the videos individually without discussing the results with other raters and/or colleagues. Raters were asked to individually select 10–15 minutes of each lecture, contemplating both monologic and dialogic parts of the lecture, and to provide a holistic assessment, as well as to look at the following items, as defined by the sub-group: range, accuracy, fluency, interaction, addressing audiences, coherence, phonology, and mediation.

## 5 (Dis)fluency measures

As stated above, one sub-group of researchers selected portions of ten lectures on which to carry out (dis)fluency analyses. The speech samples used for analysis were taken from two parts of each lecture and each sample lasted 180 seconds. The first part (A moments) occurred within the first 10 minutes of the lecture, whereas the second part (B moments) occurred between minute 25 and minute 45 of the lecture. Only moments when lecturers were in lecturing mode were selected, defined as moments when lecturers were providing explanations, examples or definitions, rather than interacting with students.

In line with Martin-Rubió (2021), the (dis)fluency measures were calculated as follows. The two 180-second audio files from each lecture were opened in the software Audacity, and three kinds of chunks were identified: 1) between-pauses units (bp-units), i.e., stretches of syllables between pauses often referred to as runs in the literature; 2) filled pauses, i.e., sounds employed as hesitation elements irrespective of length; and 3) silent pauses, i.e., silent gaps of 0.25 seconds or longer.

<caption>**Figure 1**</caption>

*MSR in A Moments and B Moments of the Ten Lectures*

<figure><img src="image_55.png" /></figure>
The measures used in the current analysis were taken from Ginther et al. (2010), and fall within three categories. The first category is Total Response Time, which is normally an important quantity measure. It is always 180 seconds in this case, so the focus is rather on the total number of syllables produced in those 180 seconds (see Appendix). The second category of measures includes three fluency measures: 1) Mean Syllables per Run (MSR) represents the average numbers of syllables produced between pauses (both filled and silent) and is calculated by dividing the total number of syllables by the number of runs; 2) Rate of Speech Time (ROST) measures the speed at which syllables are delivered and is calculated by dividing the number of syllables by the Speech Time; and 3) fluency ratio measures: Speech Time Ratio (STR), Silent Pause Time Ratio (SPTR), and Filled Pause Time Ratio (FPTR) indicate the proportion of time (in percentages) which the lecturer spends delivering meaningful syllables, silent-pausing or filled-pausing. Finally, the third category of measures includes two disfluency measures, x/100 syllables: 1) repetitions; and 2) false-starts and self-corrections (see Appendix for the main fluency and disfluency measures, together with the CEFR level and total number of syllables). This paper will now focus on the MSR measures, to show how one fluency measure is not sufficient to determine proficiency level.

The distribution of MSR in moments A and B, based on the CEFR level of the 10 lecturers, is shown in Figure 1 above. Lecturer 20 (L20), who is at C2 level according to the TAEC group's rating, has the highest MSR score (stretches of more than 16 syllables on average). He is followed by five lecturers at C1 level, and L15 and L30, who are at B2 level. Only L08 and L22 seem to diverge from the general alignment because, although L08 is at C2- level, his MSRs are lower than most lecturers at C1 level. L22's MSRs, on the other hand, are lower than one of the B2 level performances although he is at a C1 level.

<caption>Figure 2</caption>

Syllables and Runs for A Moments in the Lecture

<figure><img src="image_56.png" /></figure>
Figures 2 (above) and 3 (blow) represent the progression of the production of syllables throughout the 180 seconds in each of the two speech samples (A and B moments). In these figures, the cumulative number of syllables appear on the y-axis, whereas the runs appear on the x-axis. For instance, the A moments of lecturers L15 and L30 (Figure 2) start with a similar pattern. However, between runs 27 and 32, L15's production of syllable increases more rapidly (see Figure 2; the dark green line 15a and the light orange line 30a). The production flattens out for a few runs, but it goes up again in runs 44–45 and in runs 56–57.

In the end, L15 produces 530 syllables in 60 runs (MSR of 8.83 syllables/run), whereas L30 maintains the same pace and ends up producing 392 syllables in 65 runs (MSR of 6.03 syllables per run). In the B moments of these two lecturers (see Figure 3), though, both follow a very similar pace and in fact end up producing almost the same number of syllables in the same number of runs, L15 produces 476 syllables in 61 runs (7.80 syllables per run) and L30 produces 446 syllables in 60 runs (7.43 syllables per run).

<caption>Figure 3</caption>

Syllables and Runs for B Moments in the Lecture

<figure><img src="image_57.png" /></figure>

Overall, the three fluency measures align well with the CEFR ratings. The results suggest that one fluency measure may not be sufficient to understand the role of fluency in lecturers’ proficiency. For example, MSR is considered an important indicator of proficiency because of the assumption that lower proficiency level speakers cannot produce many syllables between two pauses, because their speech production is not automatised. In other words, they need to pause often in order to retrieve and articulate the necessary linguistic structures. If only MSR is taken into consideration, then L08’s assessment at C2 level seems inconsistent with his MSR, which seems lower than most lecturers rated at C1 level. However, when ROST is considered, then it becomes apparent that he is able to produce more utterances within the same time slot than the lecturers at C1 level. The speed of his production suggests that his speech is automatised, and he does not need time to retrieve the linguistic structures he needs to express himself. One may hypothesise that he uses frequent pauses to allow the listeners to process
information before he proceeds. Therefore, it is recommended that fluency analyses of EMI
lecturers include more than one fluency variable.

## 6 Lecturer 28 and epenthetic vowels

In this section, the A and B moments of L28 are looked at in greater detail. Excerpts from this transcription were discussed in the seventh TAEC meeting. It had been agreed that the TAEC members of one institution would transcribe the lectures from the same university, which meant that researchers would transcribe lecturers with accents that are familiar to them. Lecturer 28 was rated with a C1 level, and she had the second highest ROST, only behind the lecturer rated C2. However, there was a feature of her speech that had an impact on how these measures were to be calculated. She very often produced epenthetic vowels after final consonants. Figure 6 shows these two extra sounds after the consonants /z/ and /d/ in the words /bɪ'kɒz.ə/ and /'fɑɪ.də/. As Duguid (2001) explains, final consonants are rare in Italian, so they are often given “a following vowel, usually a *schwa*” (p. 76). More generally, “the stress-timed patterns of English cause great difficulty to Italian learners”; as a result, “[Italian] learners will expect full value to be given to all syllables” (p. 77).

<caption>**Figure 4**</caption>

*Extra Vocalic Sounds in L28's Lecture*

<figure><img src="image_58.png" /></figure>

When this feature was brought up in the seventh TAEC meeting, and it was suggested that this could be considered a mispronunciation, the Italian TAEC members objected. This was simply a feature of the Italian accent when speaking English, they argued. However, not all Italians add vocalic sounds in this fashion when speaking English, for example the Italian TAEC members present in the meeting. These extra vowels, irrespective of the reason why the Italian speaker was resorting to them, were de facto acting as filled pauses. Once it was agreed this could never be considered an error, it was decided that they could, however, be regarded
as filled pauses. The measures provided in the Appendix were calculated with this criterion in mind — filled pauses, not errors. To summarise, data coding was impacted by different ideas of how to categorise this epenthetic vowel — whether as an error or as a feature of accented speech. This in turn reflects the influence of listener background (see Cutler, 2000; Kang et al., 2019).

## 7 Discussion

The goal of this study was to analyse the use and interpretation of (dis)fluency measures for ten EMI lecturers across Europe, as well as to examine the pronunciation accuracy of one lecturer. The (dis)fluency analysis shows that, overall, all three fluency measures (MSR, Ratios and ROST) align only partially with the CEFR proficiency levels assigned by the raters, who assessed the EMI lecturers' performance based on ten items, including fluency and language accuracy. Accent was not supposed to be an item in the rating, but L28 is categorised as B2 level in the phonology item, whereas she is rated C1 or C2 for all the other items. She shows some deviations in vowel and consonant pronunciation, and many filled-pauses. Her pronunciation is a crucial aspect of her teaching, given that 20% of her students were international, (from Eastern European, Asian and African countries); her Italian-accented English will need to be intelligible to these students, not just to her Italian students.

Jensen and Thøgersen (2017) found that although accent has been shown to have little impact on intelligibility in simple tasks, accented-speech could pose difficulties for students attending an EMI lecture, as the cognitive load of lectures can already be quite high. Valcke and Pavón (2015) state that "the ability to pass on academic content effectively greatly depends on the use of proper communication strategies, among which adequate pronunciation for the achievement of comprehension" (p. 336). They support this claim by giving examples of students' comments who point out that they find it difficult to understand their lecturer and cannot focus on understanding the content of the lecture. Similar results were obtained by Yildiz et al. (2017), as students reported difficulty understanding their lecturer because of pronunciation issues.

The findings from this study highlight the tension between requiring pronunciation to be either intelligible or at least minimally accented — which could be interpreted as requiring nativelike pronunciation (see Levis, 2005). When deciding whether intelligibility is an appropriate goal in a specific EMI context, the circumstances surrounding interactions should be taken into account. As Hynninen and Solin (2018) explained, scenarios in which English is used as a lingua franca differ. Tourists ordering a meal in a restaurant abroad differs significantly from an EMI context: in the latter, English is being employed by a content lecturer specialised in a field who is providing students with complex explanations, definitions and using terminology that is new for the students, who sometimes have different L1s and English levels. In this regard, Mauranen (2011) distinguished ‘users’ from ‘learners’, and although it is obvious that all learners are users and that learning is a lifelong process, the distinction can be helpful to separate these two realities. If one’s priority is to successfully complete a transaction (say, agree on what to have for dinner), then using a variety of ways to refer to a type of food might suffice/be effective. However, when one’s goal is to learn a new disciplinary concept for future use, then the type of pronunciation through which one accesses the concept might be highly significant. The insights provided here about how lecturers’ pronunciation is assessed, should inform training courses, always bearing in mind that this is just one of the many elements lecturers must bring to their teaching.
## References

Council of Europe (2018). *Common European Framework of Reference for Languages: Learning, teaching, assessment companion volume with new descriptors*. Strasbourg: Language Policy Division.

Cutler, A. (2000). Listening to a second language through the ears of a first. *Interpreting*, 5(1), 1–23.
https://doi.org/10.1075/intp.5.1.02cut

Dimova, S. (2018). Linking the TOEPAS with the CEFR: Technical report.
https://cip.ku.dk/english/documents/Alignment_of_TOEPAS_with_the_CEFR.pdf

Duguid, A. (2001). Italian speakers. In M. Swan & B. Smith (Eds.) *Learner English: A teacher's guide to interference and other problems* (pp. 73–99). Cambridge University Press.

Ginther, A., Dimova, S., & Yang, R. (2010). Conceptual and empirical relationships between temporal measures of fluency and oral English proficiency with implications for automated scoring. *Language Testing*, 27(3), 379–399.
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Hynninen, N., & Solin, A. (2018). Language norms in ELF. In J. Jenkins, W. Baker, & M. Dewey (Eds.) *The Routledge handbook of English as a lingua franca* (pp. 267–278). Routledge.

Jensen, C., & Thøgersen, J. (2017). Foreign accent, cognitive load and intelligibility of EMI lectures. *Nordic Journal of English Studies*, 16(3), 107–137.
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Kang, O., Thomson, R., & Moran, M. (2019). The effects of international accents and shared first language on listening comprehension tests. *TESOL Quarterly*, 53(1), 56-81.
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Levis, J. (2005). Changing contexts and shifting paradigms in pronunciation teaching, *TESOL Quarterly*, 39(3), 369–377.

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Martin-Rubió, X. (2021). Audacity and Praat as pedagogical tools: Analysing fluency and pronunciation accuracy, *Philologia*, 19(1), 37–50.
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# Appendix

## The Main (Dis)fluency Measures per Lecturer, at A Moments and B Moments

<table><thead><tr><th rowspan="2">L</th><th colspan="2">syllables</th><th rowspan="2">level</th><th colspan="2">MSR</th><th colspan="2">ROST</th><th colspan="2">STR</th><th colspan="2">repetitions</th><th colspan="2">FS/SCs</th></tr><tr><th>A</th><th>B</th><th>A</th><th>B</th><th>A</th><th>B</th><th>A</th><th>B</th><th>A</th><th>B</th><th>A</th><th>B</th></tr></thead><tbody><tr><td>L04</td><td>613</td><td>545</td><td>C1</td><td>10.57</td><td>10.48</td><td>4.40</td><td>3.93</td><td>77.10</td><td>76.21</td><td>1.14</td><td>2.02</td><td>1.47</td><td>2.02</td></tr><tr><td>L06</td><td>561</td><td>578</td><td>C1</td><td>10.58</td><td>9.97</td><td>3.75</td><td>3.94</td><td>82.30</td><td>79.82</td><td>0.18</td><td>0.35</td><td>0.53</td><td>0.52</td></tr><tr><td>L08</td><td>622</td><td>647</td><td>C2-</td><td>9.28</td><td>9.80</td><td>4.41</td><td>4.71</td><td>78.14</td><td>81.88</td><td>0.80</td><td>0.93</td><td>0.48</td><td>0.46</td></tr><tr><td>L11</td><td>608</td><td>627</td><td>C1</td><td>10.31</td><td>11.61</td><td>4.12</td><td>4.39</td><td>81.23</td><td>78.23</td><td>0.66</td><td>0.48</td><td>1.32</td><td>1.12</td></tr><tr><td>L15</td><td>530</td><td>476</td><td>B2</td><td>8.83</td><td>7.80</td><td>3.81</td><td>3.52</td><td>76.21</td><td>73.71</td><td>2.26</td><td>2.73</td><td>2.08</td><td>1.47</td></tr><tr><td>L18</td><td>588</td><td>580</td><td>C1</td><td>13.36</td><td>11.37</td><td>3.88</td><td>4.13</td><td>82.98</td><td>77.96</td><td>1.87</td><td>1.55</td><td>0.85</td><td>1.72</td></tr><tr><td>L20</td><td>773</td><td>812</td><td>C2</td><td>16.10</td><td>16.92</td><td>4.96</td><td>5.14</td><td>86.40</td><td>87.37</td><td>0.78</td><td>0.99</td><td>0.52</td><td>0.37</td></tr><tr><td>L22</td><td>506</td><td>506</td><td>C1</td><td>8.03</td><td>8.30</td><td>4.28</td><td>4.13</td><td>65.65</td><td>67.64</td><td>0.40</td><td>0</td><td>1.13</td><td>0.40</td></tr><tr><td>L28</td><td>696</td><td>712</td><td>C1</td><td>10.55</td><td>11.67</td><td>4.57</td><td>4.66</td><td>83.34</td><td>84.20</td><td>1.01</td><td>0.28</td><td>0.86</td><td>0.98</td></tr><tr><td>L30</td><td>392</td><td>446</td><td>B2</td><td>6.03</td><td>7.43</td><td>2.92</td><td>3.31</td><td>74.12</td><td>74.64</td><td>1.28</td><td>1.12</td><td>1.79</td><td>2.02</td></tr></tbody></table>

Note. L = Lecturer

## About the author

Xavier Martin-Rubió holds bachelor degrees in English Philology and Audiovisual Communication from Universitat de Lleida, and a Master's degree in European Studies from Maastricht Universiteit and University of Portsmouth. He defended his doctoral dissertation in April 2011. He worked as an English teacher in a high school, two official language academies and two private universities before moving back to Universitat de Lleida. He started working full-time at UdL in December 2014. He has been involved in four competitive projects as a member of CLA, and after a gap of several years, he is publishing again on EMI in higher education, beliefs and emotions in additional language learning, and fluency and accuracy measurements across tasks.

Email: xavier.martinrubio@udl.cat
# L2 pronunciation: Seven learning/teaching paradigms found in instructed learning

Piers Messum
Pronunciation Science Ltd.

Roslyn Young
Pronunciation Science Ltd.

For good production in L2 pronunciation, learners have to be able to form new sounds in many syllabic contexts and at speed, so pronouncing an L2 requires learning new motor skills. The basic unit of motor skill development is the action-perception cycle, within which there is a need for the learners' attempts at a target to be evaluated, by themselves or by an expert. We present a theoretical framework based upon how learning/teaching paradigms meet the need for such evaluation. This yields a taxonomy of seven paradigms.

**Keywords:** L2 pronunciation learning, taxonomy, L2 speech sound production, motor skill

<figure><img src="image_59.png" /></figure>
# 1 Introduction

For many years, we have been concerned that classroom-based pronunciation teaching has been developed, practised, and researched without sufficient prior investigation into how learners learn to pronounce an L2. Others have made similar points. For example, Foote and Trofimovich (2018) describe a lack of theory to guide L2 pronunciation research as being one of the most acute problems in the field. They explore how linguistic, psychological, interactionist, sociocultural, identity and sociocognitive perspectives can be useful for research, but acknowledge firstly that these have little to contribute to L2 pedagogy and secondly that this is a significant shortcoming, because, “research in L2 pronunciation should ultimately inform pronunciation teaching” (p. 85). For theory to support pronunciation teaching, it seems clear that it should address how learners learn to pronounce an L2.

This article starts to address one aspect of this issue: learning to produce L2 speech sounds which are not present in the L1 inventory (e.g., the production of English /l/ and /r/ by Japanese speakers, or French /y/ by English speakers). When we refer to learning new L2 speech sounds, we include learning new sounds in different contexts, not just in isolation (i.e., the learner producing sounds, sounds within clusters, sounds in words and then in phrases). Pronouncing an L2 sound, therefore, requires developing new motor skills.

It is obvious that one should try to understand how something is learnt before teaching it, so why is the mechanism used in learning to pronounce L2 so rarely discussed by researchers? Presumably the issue has seemed to be unproblematic: teachers and researchers know that some forms of vocal learning in speech and singing can be done by imitation (by which they mean a self-evaluated auditory matching-to-target process) and assume that this is possible for L2 speech sounds. They may think that children learn L1 pronunciation in this way, and that we can invoke the same mechanism in older learners, albeit with teaching practices that are adapted to take account of differences between the two age groups (summarised by Strevens, 1974).

The field in general, both researchers and teachers, has thus assumed that learners will develop L2 pronunciation if they are presented with exemplars to be copied. In so-called Intuitive-Imitative (I-I) approaches (Celce-Murcia et al., 2010; Kelly, 1969), this is imagined to be sufficient. In Analytic-Linguistic (A-L) approaches, this stage is preceded by training to improve how learners hear L2 and/or with phonetic information and rules which, it is believed, will become know-hows (automatised procedural knowledge) through repeated application.

We have identified six other ways in which it has been or could be imagined that L2 pronunciation is learnt/taught. To create this taxonomy, we approached the problem from two directions. First, we asked, “Since L2 pronunciation is a socially transmitted motor skill, what are the implications for how it is learnt?”, and then, “L2 pronunciation is taught in different ways; what are the learning mechanisms that can be inferred to underlie each of them?”.

We start by outlining some conceptual points drawn from psychology and other disciplines which inform our approach (see §2). We describe the basis of our taxonomy (see §3), and then we describe the different learning mechanisms it identifies and the teaching practices which are based upon them (see §4–6).

# 2 Conceptual points for understanding pronunciation learning

Messum and Young (2021) gave reasons why learning to pronounce an L2 is “a highly unusual activity” (p. 170) among socially transmitted skills, including the fact that the actions involved are largely invisible and that production and perception skills developed for L1 pronunciation interfere with the process. Furthermore, we argue that five conceptual points need to be taken into consideration if one is to think clearly about learning to pronounce an L2. These are presented one by one in the following sub-sections.
## 2.1 Pronunciation learning is not imitation

When teachers provide a spoken model for their learners in pronunciation classes, they are presenting them with the results of their actions and not the actions themselves, since most of the actions involved are hidden inside the mouth. In this way, teaching pronunciation is unlike teaching most skills, where a model shows the learner what the demonstrator is doing as well as the result. Metaphorically speaking, if a winner of the Masters were teaching golfers how to drive a ball by simply striking 300-yard shots off the tee, we do not think they would learn as much as if he gave them advice on how to improve their own swings. But at least they might pick up something from watching him in action. Now imagine if he were hitting those 300-yard drives while standing behind a tarpaulin so that the golfers could not see what he was doing and could only see the result: a ball sailing down the fairway every time he produced a 'model'. Then they would get very little, if anything, from the experience.

In technical discussions, imitation refers to copying of actions as well as reproducing the demonstrator's results. For this reason, the colloquial use of the word imitation for the result of a self-evaluated matching-to-target process in L2 pronunciation is inappropriate. The field should be using the word emulation, or more strictly, goal emulation: the adoption of the goals of the demonstrator, the reproduction of his/her results but not the copying of his/her actions (Call & Carpenter, 2002; Whiten & Ham, 1992). It is important for us to use terminology that acknowledges the complexity of the process of learning L2 speech sounds. In imitation, there are two sources of information that the learner can attend to at will: the actions of the model and the results obtained. In emulation, there is only one source, the results, and for L2 speech these are an acoustic signal whose interpretation by most learners is distorted by the mechanism of their L1 perception.

## 2.2 Two ways of listening: Autocentric and allocentric

There has been a longstanding scientific interest in the two products of our senses, sensation and perception, and in their relation. Humphrey (1992) opens his discussion of this by quoting Reid (1785): "The external senses have a double province – to make us feel, and to make us perceive" (p. 46).

In the auditory domain, Öhman (1975) gives the following example: we might experience a household event either as the sound of a refrigerator door shutting in another room or as meaningless "concrete music", that is not about the state of the world but is "an immediate awareness of the developing states of [our] auditory sense" (p. 42). Similarly, when listening to a speech sound, it is possible to attend to it in two different ways: as something meaningful or as noise. For instance, we might experience an event as a linguistic /p/ or as the meaningless noise of an explosion of air from the mouth. Since the first way of attending to sounds gives us potentially useful information about the outside world, it is the attentional set that we use almost all the time. Indeed, when meaning is available from a signal, it is often difficult to attend to it as noise.

In research on speech perception, various distinctions have been drawn between the attentional sets of listening, and a variety of terms have been used to describe them. There have even been proposals for three-factor models of speech perception, with auditory, phonetic, and phonemic components (Werker & Logan, 1985). However, to describe the particular distinction that Öhman (1975) drew and to avoid any possible confusion with other distinctions that have been made, we will use the terms proposed by Schachtel (1959), i.e., *autocentric* for awareness of sensations and *allocentric* for meaningful perception. These terms capture the point that the experience of mere noise is an awareness of the state of our own auditory sense
(autocentric mode) while experiencing meaning is an awareness of the state of the outside world (allocentric mode).

It is necessary to make this distinction when considering pronunciation because speech sounds (instances of phonemes, or strings of phonemes) are noises to which we give linguistic significance in speech. When we learn a new L2 sound we are learning to produce a noise (or set of noises) that will be recognised as that particular sound by other speakers of the L2.

## 2.3 Two forms of memory: ASM and ALTM

Current models of memory distinguish short-term and long-term memory, and posit at least two components of short-term memory that deal with sound (Scott & Mishkin, 2016). The first is a phonological store that can be supplemented with subvocal rehearsal to sustain speech representations. However, this is not of any obvious use in learning to produce new L2 sounds.

The second is auditory sensory memory (ASM), which Nees (2016) describes as “a set of acoustic features organized in time that can be consulted to complete behavioural tasks, including comparing sounds to one another” (p. 1). There is a panoply of other names in use: the sensory register, echoic memory, acoustic short-term memory, passive short-term memory, pre-perceptual auditory memory, and so on. ASM is reported as decaying rapidly, usually within a few seconds (Nees, 2016).

Auditory long-term memory (ALTM) may also be relevant to learning new L2 sounds. As it is usually conceived, it does not store raw, sensory intake (noises). However, since selective attention is considered to isolate information in perception and then store it in long-term memory (Barsalou 1999), there does not seem to be a principled reason against any detail at any level being captured in ALTM (e.g., a novel feature of an L2 sound), provided the learner has noticed it.

## 2.4 Perceptual representations are not production representations

One determiner for what is captured in long-term memory is the current task, since a task is a driver for selective attention. If the task is to learn to identify or discriminate any type of object, then the abstraction will be optimised for that purpose, but not necessarily structured for recall or to guide subsequent production. Perceptual training in L2 pronunciation is usually evaluated by the success of learners in identifying or discriminating new L2 sounds. However, this cannot be taken to mean that they have developed a type of representation that can directly inform production.

To better appreciate this point, we suggest you stop reading and, from memory, draw the Ford Motor Company logo, trying in particular to get the style of the lettering right. Despite your undoubted ability to recognise this logo (which you have probably seen thousands of times), and to discriminate it from similarly coloured or shaped logos, you would be unusual if your production of the <f> or <r> matches the detail of the original. In any perceptual modality, to be able to recognise something does not mean one knows how to produce it.

## 2.5 Mirroring: Learning through others

Before video recording technology was available, springboard divers had to rely upon a coach to evaluate their performance and hence to improve. The coach acted as a form of mirror to the learner, and psychology has demonstrated many ways in which we learn about ourselves through mirroring interactions. Moreover, it is very possible that children’s L1 pronunciation develops this way, during vocal exchanges in which their caregivers imitate their babbling, reformulating it into well-formed L1 speech sounds (Messum & Howard, 2015). Munhall et
al. (2021) lend support to this hypothesis, considering it to be consistent with current thinking on how speech perception develops in children.

Maas et al. (2008) use the terminology of Schmidt’s (1975) schema theory (discussed below) to describe this mechanism:

> Before the recognition schema can be used to judge the accuracy of the movement, the system must first learn which sensory consequences are to be considered “correct.” There is often a clear reference of correctness (e.g., a golf ball must end up in the hole), but there are cases in which the reference of correctness is not directly available or interpretable to the learner but instead depends on feedback from an instructor, such as when learning to perform a somersault in diving. In such cases, the learner must calibrate the expected sensory consequences with an externally provided reference of correctness, so that the internal error signal may serve to correct errors on future trials without external feedback. (p. 279)

The reference of correctness for L2 speech sounds may be neither directly available to learners nor interpretable by them: *unavailable* because of the perceptual opacity of speech sounds (Heyes & Ray, 2000), with the learners hearing their own voice mixed in with bone-conducted sound and hearing what they expect themselves to be producing rather than the actual output (Munhall et al., 2021); and *uninterpretable* because of the effect of their L1 listening expertise on how they hear L2. In these circumstances, an externally provided reference of correctness becomes necessary.

## 3 A taxonomy of L2 pronunciation learning/teaching paradigms

Now that these conceptual points have been made, we present seven mechanisms for how the production of L2 speech sounds might be developed through conventional learning, with a note in most cases of an associated teaching practice or practices (Figure 1). A more comprehensive taxonomy will include learning mechanisms proposed in the literature that invoke innate, neural capacities (Messum & Young, in preparation).

Before discussing each mechanism in turn, we first explain why our main taxonomic question is how a speaker evaluates their attempts at L2 pronunciation.

While the learning and teaching of L2 pronunciation can be considered from various perspectives, there should be a common aim: that learners pronounce L2 proficiently. Learners have to develop new willed actions — do something different with themselves (i.e., with their articulatory apparatus) — if they are to pronounce L2 differently from how they pronounce L1. Pronouncing is a motor skill. With this starting point, we can broaden our understanding of L2 pronunciation learning by reference to the established body of research on motor skill development.

The foundational theories in this field — Closed-loop Motor Learning (Adams, 1971, 1987) and Schema Theory (Schmidt, 1975; Schmidt & Lee, 2005) — agree that action and evaluation are two key elements in motor learning. These inform the memory trace and perceptual trace respectively in Adams’ theory, and the recall schema and recognition schema in Schmidt’s. In repeated action-perception (A-P) cycles (Cutsuridis et al., 2011), learners develop sensorimotor contingencies between their actions and the results these produce. The action part of the cycle relies on the learner having some control over what they do: the ability to do the same thing again or to do something new. In the perception part of the cycle the learner evaluates the results of the action judged against the target. This evaluation can be performed either by the learner, or by a competent other person who communicates their evaluation.
<caption>Figure 1</caption>

A Taxonomy of Learning/Teaching Paradigms in Instructed L2 Pronunciation

<figure><img src="image_60.png" /></figure>

*Note.* The labels within the numbered boxes describe what a learner does in each case, with the name of an associated teaching practice noted if appropriate. Abbreviations: I-I, Intuitive-Imitative; A-L, Analytic-Linguistic. M, Model; A, Attempt. (Thus ‘M-A’ means ‘model followed by learner attempt’.)

Before the first attempt is made, the learner has a (perhaps unspoken) question, “How can I do this?”. After the attempt, they need to answer the question, “How successful was that?”. If they continue, they then have to ask, “What am I going to do now?” and, after the next attempt, “Was that better or worse than last time?” and “What difference did the new thing I tried make?”.

To establish the possible learning mechanisms for L2 pronunciation, we focus on the perception/evaluation side of the A-P cycle. Thus, our taxonomic question on the left of Figure 1 asks how the learner evaluates their attempts at pronouncing an L2. The possible ways in which this could be done are documented on the three branches which lead away from the central question and which describe the learner's mental activity:
1. The learner compares *sensory* images: the image they retrieve from their own attempt that they compare to a model they hear. One (or perhaps both) of these would be held in ASM.

2. The learner is informed about their attempt from another's evaluation of it — be it from a teacher, another speaker of the L2, or some form of technology.

3. The learner evaluates their attempt using *knowledge* previously acquired. This knowledge might be: a) auditory criteria for correctness for the L2 sound; b) a fine-grained exemplar of the sound in ALTM that they use for comparison; or c) motor and sensory (proprioceptive) criteria for correctness. The knowledge needed for a) and b) would have been acquired through listening; that for c) would have been acquired from previous cycles of A-P learning.

Note that any actual classroom interaction might give the learner more than one source of information about their performance, but the sources will be drawn from these three basic categories.

The final termination points for the three branches from the central question in Figure 1 are seven learning/teaching paradigms for L2 pronunciation, labelled 1a to 3c. The boxes describe what the learner does in each case, with the name of an associated teaching practice noted if appropriate. The next sections (§4–6) explain the paradigms resulting from each of the three branches.

# 4 Paradigms 1a, 1b, and 1c: Comparison of sensory images

## 4.1 Listen First: Intuitive-Imitative and Analytic-Linguistic approaches (Paradigm 1a)

If the learner evaluates their performance based on a comparison of sensory images (the aural image created by their attempt at a sound and an aural image they hear as a model) then the most familiar classroom order of such events (and the usual order of such events in language learning apps on mobile phones) is that of Listen & Repeat: a model followed by a learner attempt. This is the exercise that best characterises Intuitive-Imitative (I-I) pronunciation teaching.

However, learners complain that they cannot *hear* the model, i.e., that they are not aware that the model L2 token is different from some similar sound in L1. Nothing can be achieved by asking them to copy what they do hear in these circumstances, so teachers seek ways to remedy this. Hence Analytic-Linguistic (A-L) approaches supplement the supposed natural mechanism of imitation with phonetic information and/or preparatory perceptual training. A-L practices are considered to complement I-I practices rather than replace them (Celce-Murcia et al., 2010). However, to acknowledge that the learner's response after A-L preparation is likely to be more carefully considered than what they can attempt in simple Listen & Repeat, we call it Listen & Say.

Whether or not there is a preparatory phase, notice that the principal learning move for production in both I-I and A-L approaches is for the learners to match an L2 sound which has been presented to them. These two Listen First approaches aim at a learner's ASM, through autocentric mode listening. Most current classroom practice is therefore based within this single paradigm in our taxonomy.
## 4.2 Say & Listen (Paradigm 1b)

It is possible to reverse the order of events in Listen First approaches, i.e., for the model to follow the attempt. For example, in the Human Computer technique from Community Language Learning (Curran, 1976), the teacher repeats the learner's sound, word or phrase in their own, correct L2. The learner is then not allowed to repeat the phrase after the teacher.

This prohibition on repetition prevents reflexive copying where the learner is not aware of their speech motor activity, i.e., what they themselves are doing to pronounce. Instead, there is a period of silence, in which the learner can compare the image they have of their own production to what they have just heard. This gives them the opportunity to evaluate the former and consider what they might change about it. When enough time has passed for the teacher's utterance to have faded from the learner's ASM, the learner is allowed to say the phrase again, informed by what they learned from the previous cycle. The teacher will repeat the phrase again in good quality L2, and the learner has the opportunity to compare and contrast the two renditions.

## 4.3 Choral repetition (Paradigm 1c)

In choral repetition, the teacher's model comes neither before nor after the learner's attempt, but rather in both places. In repeated, rapid sequences of model – attempt – model – attempt, it becomes unclear which of the mechanisms in boxes 1a and 1b describes the learning episode. Choral repetition of this type could involve either of them, depending upon how the learner chooses to direct their attention, potentially switching between the two more than once during any session.

Kjellin (2004) describes his rationale for choral practice led by the teacher, and his own classroom methodology that implements this. Based upon extensive classroom experience, he insists that 10, 20 or 30 repetitions of a phrase are inadequate and counterproductive, but that a block of 50-100 repetitions leads to success. Jones (2018) describes her own rationale and gives further advice on the use of choral repetition.

Immonem et al. (2022) report success training 7-year-old children to produce new L2 vowels using this learning/teaching paradigm: automatic, alternating presentation of two words containing the vowels with a fixed interstimulus interval of three seconds, over four training sessions of 30 pairs of repetitions. With similar training regimes, older children and adults have also been successful, but more slowly. It might be that younger children are better at attending to sounds as sensory objects and to be less deeply in the *grip* of L1 (Underhill, 2013).

# 5 Paradigm 2: Use of external expert judgement

In Paradigm 2, Say & Adjust, learners rely on the evaluation of their performance by an expert other: a metaphorical *mirror*. Within a mirror learning mechanism, it is acknowledged (and unproblematic) that the learners do not yet know the target: either how to create it, what it feels like or even what it sounds like. They only have some approximate idea that enables them to start production. With feedback from an expert, they can modify what they do, all the while getting to know the target better.

Sixty years of classroom practice has demonstrated the efficacy of such a process in L2 pronunciation teaching, starting with Gattegno's first version of the Silent Way and developed by him and other teachers since (Messum & Young, 2021). The paradigm need not be associated with the Silent Way. The empirical evidence presented by Warsi (2001) suggests that he was considerably more successful than Bradlow et al. (1997) in teaching the production of English /l/ and /r/ to Japanese learners through Say & Adjust. Furthermore, the source of
evaluation need not be human; technological evaluation and feedback can also be used (e.g.,
Kartushina et al., 2015; Sakai, 2016).

While the Say & Adjust paradigm is consciously deployed in Silent Way classes, it may
also appear in conventional classes which seemingly employ a Listen First approach. When a
teacher says, “Make a [...]” and the learner takes what they hear to be a *cue* rather than a *model*
(and this distinction is key), they ignore the possibility of copying what the teacher has said
and produce their current best attempt at the sound. Then, when the teacher gives feedback on
how well the learner has done, informing a new attempt, this is a Say & Adjust exchange.

## 6 Paradigms 3a, 3b, and 3c: Applying knowledge to output

Three other paradigms involve self-evaluation based upon knowledge acquired previously. This notion can also be found in the field of Child Phonology. For example, based on developmental data, Kuhl (2000) described one way in which young children may learn to produce L1 speech sounds: “... early in life, perceptual representations of speech are stored in memory. Subsequently, these representations guide the development of motor speech” (p. 11854).

An analogue of this for L2 was described by Bradlow et al. (1997): “... perceptual learning leads to more accurate internal acoustic representations of the target speech sounds, and these improved representations function as acoustic templates that play an important role in monitoring the articulatory output” (p. 2307). They called such templates *output monitors*.

A monitor of some type, operating to evaluate the speaker’s own output, could rely upon
any of three distinct types of previously acquired knowledge: recognition criteria, a recalled
image, or motor and sensory criteria.

### 6.1 Self-evaluation based on recognition criteria (Paradigm 3a)

The speaker might have developed criteria to identify and/or discriminate L2 sounds produced
by others (in isolation or in words) which they now apply to evaluate their own output. To
return to the visual analogue involving the Ford logo, a novice illustrator trying to reproduce it
without a model to copy might evaluate their attempt by wondering whether it looks right.

### 6.2 Self-evaluation based on a recalled image (Paradigm 3b)

The speaker might have developed an image of the L2 sound which is now stored within ALTM. They could compare their output against a version of this that they recall. With respect to the Ford logo, the novice in this case would be able to evoke (or recall) a detailed mental image they had created to guide their attempt.

### 6.3 Self-evaluation based on motor and sensory criteria (Paradigm 3c)

During previous work on the L2 sound, the speaker might have developed some or all of three
different types of criteria that now help them during independent practice. They will know
more about: 1) how (gesturally) to make the sound (i.e., what actions they need to perform); 2)
how it feels to make the sound; and 3) how it sounds to them to make the sound.

These criteria alone do not allow them to exceed their best previous level of production
accuracy, but they do allow them to consolidate their learning: producing the sound in different
contexts, at different rates, with greater automaticity, etc.
Returning to the Ford logo, in this case the novice would have already drawn the logo several times, checking their attempts against an original, and hence developing facility and accuracy in its production. Now they are making a further attempt.

## 7 Conclusion

Our taxonomy is based on the characteristics of the perception side of the A-P cycle; specifically, the mechanism by which a learner evaluates their successive attempts. We have identified a number of possible evaluation mechanisms and the teaching approaches that rely upon them which, considered together, we call learning/teaching paradigms. This taxonomy will be expanded (Messum & Young, in preparation) to include paradigms that do not rely upon instruction, and we will also discuss the likely effectiveness of each of them.

As suggested by Pennington (2021): “... approaches that challenge standard practices on theoretical grounds deserve to be systematically investigated and their effects and effectiveness compared to those of the standard practices” (p. 17). The taxonomy presented here shows that there are plausible learning/teaching paradigms other than Listen First and technology-driven approaches. We support Pennington’s call for researchers to investigate the effectiveness of these currently non-standard practices.

## Acknowledgements

We would like to thank our two anonymous reviewers from EPIP 7, as well as Marc-Georges Nowicki, Alice Henderson, Dan Frost, Anastazija Kirkova-Naskova, Martha Pennington, Jonathan Marks, and Adrian Underhill.

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**About the authors**

**Piers Messum** has taught English in Japan, France, and the UK. His PhD in Phonetics from University College London investigated how children learn L1 pronunciation. He co-authored *How We Learn and How We Should be Taught* (2011) with Roslyn Young. He now teaches in London, and does teacher training and materials development for Pronunciation Science Ltd.

Email: p.messum@gmail.com

**Roslyn Young** worked at the University of Franche-Comté in the Applied Linguistics Centre from 1968 until she retired, teaching spoken English and sometimes spoken French in intensive courses. She ran her first 'pronunciation clinic' in 1978 and has worked continuously since then on ways of improving the teaching of pronunciation. She wrote her doctoral thesis on Caleb Gattegno's model of learning and its relevance to his work in language teaching. She has published numerous articles on the teaching of pronunciation and on how people learn.

Email: roslynyoung@gmail.com
# Task-based pronunciation teaching helps to improve L2 vowel production: Generalisation effects

Ingrid Mora-Plaza

University of Barcelona

A number of task-based pronunciation teaching interventions have been shown to raise learners' awareness of relevant properties of L2 speech input during interaction (e.g., Solon et al., 2017). However, it still remains unclear whether pronunciation gains are generalisable to diverse lexical contexts (unfamiliar tokens) and elicitation modes (words vs. sentences). This study investigates whether a focus on phonetic form improves learners' production of English /i: – ɪ/ and /æ – ʌ/ and leads to generalisation effects and retention. Sixty-three L1 Catalan/Spanish EFL learners carried out 20 dyadic, problem-solving tasks over 7 weeks. Task completion required the distinction of the target lexical items (e.g., *bean* – *bin*, *cat* – *cut*). Gains in production and generalisation effects were assessed through delayed word and sentence repetition tasks, and Mahalanobis distances were measured between confusable vowels and between learners' and native speakers' productions. Results showed that not only did learners increase the qualitative distance between the target confusable vowels, but their L2 vowel productions also approximated those of native speakers at post-test in words produced in isolation and in sentences. In addition, gains generalised to untaught tokens and improvement was retained after 11 weeks.

**Keywords:** pronunciation instruction, task-based language teaching, English vowel production, generalisation effects, retention

<figure><img src="image_61.png" /></figure>
# 1 Introduction

Learning foreign language (FL) phonology is an arduous task because input in formal FL contexts is generally insufficient, for instance, typically limited to a few hours of language-focused instruction per week (Muñoz, 2014) and often L1-accented. Consequently, L2 categorical perception, speech segmentation, and lexical activation and retrieval processes are inevitably affected by the already-automated L1 perceptual system. According to the Perceptual Assimilation Model (PAM-L2; Best & Tyler, 2007), L1-based perception causes difficulties in phonetic learning, especially when phonetically similar L2 sounds are perceptually mapped onto single L1 sound categories, making L2 sound contrasts confusable.

At the phonetic processing level, the English vowel contrast /i: – ɪ/ is very challenging for Catalan/Spanish speakers because they only have one single high vowel /i/ with no comparable tense–lax distinction. In PAM-L2 terms, Catalan/Spanish speakers assimilate English /i:/ and /ɪ/ (e.g., sheep – ship) to Catalan/Spanish /i/ via a category-goodness assimilation pattern. Thus, whilst the English vowel /i:/ has been found to be highly similar to the Catalan /i/, the English vowel /ɪ/ has been perceived as a poorer fit for the same L1 sound, being identified as Catalan /i/ or /e/ (Cebrian, 2021). The English vowel contrast /æ – ʌ/ is also difficult to perceive and produce for Catalan/Spanish speakers due to the presence of the Catalan low central vowel /a/ (Cebrian, 2021). PAM-L2 would classify it as a single-category assimilation, as English /æ/ and /ʌ/ are assimilated to Catalan /a/.

Despite the difficulty in developing learners’ L2 phonological awareness in a FL context, directing learners’ attention to phonetic form through various training and instructional techniques has proved effective in developing the speech perception and production of L2 learners with different proficiency levels and L2 experiences (Lee et al., 2015). Few studies have explored the role of tasks in generating a focus on phonetic form during interaction (Gurzynski-Weiss et al., 2017), as well as the extent to which L2 pronunciation gains generalise to different contexts and different speakers/voices and remain over time.

## 1.1 Attention to phonetic form

In order to acquire new speech sounds, it is indispensable for learners to notice and pay attention (Schmidt, 1990) to cross-linguistic differences between L1 and L2 phonologies. One way to achieve this is by explicitly instructing learners to attend to specific aspects of the speech input (Guion & Pederson, 2007) while ignoring others. Lab-based high-variability phonetic training (HVPT) can be used to raise learners’ awareness of L2 phonology and its gains have been shown to be robust, generalising to new lexical items and speakers (Thomson, 2018).

Drawing attention to phonological form through explicit pronunciation instruction has also been found to be effective (Lee et al., 2015), as it helps learners notice the difference between their own productions and those of more proficient L2 speakers. However, several studies have found Focus on Form (FonF) instruction to be more effective than Focus on FormS (FonFS) instruction<fnref n="1" /> in developing intelligibility, comprehensibility and L2 pronunciation accuracy (e.g., Darcy et al., 2021). Saito’s (2012) synthesis of 15 quasi-experimental studies showed that, whereas FonFS interventions resulted in improvement only at a controlled level, FonF interventions enabled learners to improve at both controlled and spontaneous speech levels.

<footnote n="1">¹ Saito (2012) refers to FonF instruction when learners practise pronunciation form while being involved in contextualised meaning-oriented communicative activities, and FonFS instruction when learners are asked to practise the accurate use of pronunciation form via mechanical drills and choral repetition.</footnote>
**1.2 Task-based instruction and pronunciation**

Task-based language teaching (TBLT), also known as task-based instruction (TBI), is a teaching approach that focuses on having learners complete meaningful tasks using authentic language input. It aims to draw their attention to a particular linguistic structure during interaction, with tasks specifically designed to offer opportunities for practising the target structure. It is believed that real-world interaction encourages learners to refine and restructure their inter-language by drawing their attention to linguistic code features during negotiation for meaning (Long, 2015). Following Ellis (2009), tasks may direct learners' attention to meaning while predisposing them to focus on challenging L2 phonological forms through task-essentialness (Loschky & Bley-Vroman, 1993).

Whereas most research examining the facilitative role of tasks has focused on grammar, lexical structures or pragmatics, only a few TBLT studies have investigated the effectiveness of tasks in drawing learners' attention to phonetic form during communicative task performance, by testing learners' L2 pronunciation improvement (Gurzynski-Weiss et al., 2017). Although task-based pronunciation teaching (TBPT) has been found to be beneficial for L2 pronunciation development (Mora-Plaza et al., 2018), it remains unclear to what extent TBPT helps L2 pronunciation development over time and whether gains may be transferred to new lexical contexts. Furthermore, little is known about how L2 vowel production accuracy may vary depending on the context where vowels are embedded, namely, in isolated words or in sentences (but see Mora et al., 2022).

**1.3 Research questions**

The present study extends this line of research by assessing the effects of form-focused instruction on the production of English high /i:, ɪ/ and low /æ, ʌ/ vowels in communicative decision-making tasks during a longitudinal intervention. Improvement in L2 vowel production was assessed in terms of elicitation mode and generalisation to untaught tokens. The present study is therefore guided by the following research questions:

**RQ1:** Does TBPT improve learners' production of L2 vowels embedded in words elicited in isolation?

**RQ2:** Does TBPT improve learners' production of L2 vowels embedded in words elicited in sentences?

**RQ3:** Are gains in L2 vowel production generalised to untaught tokens elicited in isolation and in sentences?

**2 Methods**

This study followed a pre-/post-test design, with a delayed post-test that learners performed 11 weeks after the task-based intervention. All participants carried out a battery of perceptual (discrimination, lexical sensitivity) and production (delayed word, sentence) tasks targeting the English vowel contrasts /i: – ɪ/ and /æ – ʌ/ individually before and after 7 weeks. A language background questionnaire and an elicited imitation (EI) task were administered before the first testing session, in order to obtain learners’ biographical information and L2 proficiency level (Figure 1). In the EI task, learners were instructed to repeat 30 sentences after a beep signal. The sentences increased in grammatical and lexical complexity. Learners’ productions were recorded and assessed for accuracy following Ortega et al.’s (2002) rubrics, where each sentence received a score from 0 to 4. Individual scores could thus range from 0 to 120 points.
<caption>Figure 1</caption>

Research Design

<figure><img src="image_62.png" /></figure>

The experimental group was exposed to a series of task-based lessons three times per week. Learners dedicated the first 20–30 minutes of their English class to practising L2 reading, listening, writing and/or use of English and the last 30–40 minutes were devoted to doing pronunciation-focused oral tasks in pairs. The control group completed the pre- and post-test, and continued with their regular English classes, without taking part in any task-based intervention.

## 2.1 Participants

Ninety-two Catalan/Spanish English as a Foreign Language (EFL) learners from a public high school participated in the study. They belonged to three intact classes selected for convenience, as it would have been logistically impossible to randomly assign participants to different groups. The number of males (M) and females (F) was balanced across groups (Experimental group: M = 33, F = 30; Control group: M = 14, F = 15) and their age ranged from 16 to 17 years old. Their self-estimated English proficiency level ranged from intermediate to upper-intermediate (see Table 1). The experimental and control groups were not significantly different in terms of demographic and linguistic variables (*p* > .05).
<table><caption>**Table 1**</caption><caption>Participants' Demographic and Linguistic Information</caption><thead><tr><th rowspan="2"></th><th rowspan="2">M</th><th rowspan="2">SD</th><th rowspan="2">Range</th><th colspan="2">95% Confidence Interval (CI)</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td colspan="6"><strong>Experimental group (n = 63)</strong></td></tr><tr><td>Age (years)</td><td>16.0</td><td>0.2</td><td>16-17</td><td>16.0</td><td>16.1</td></tr><tr><td>Age of onset (years)</td><td>5.6</td><td>1.9</td><td>3-9</td><td>5.2</td><td>6.1</td></tr><tr><td>L2 instruction (years)</td><td>10.3</td><td>1.9</td><td>7-13</td><td>9.8</td><td>10.7</td></tr><tr><td>L2 use (hours/week)</td><td>3.5</td><td>3.1</td><td>0-14</td><td>2.7</td><td>4.1</td></tr><tr><td>Self-estimated proficiency <sup>a</sup></td><td>6.0</td><td>1.6</td><td>1-9</td><td>5.3</td><td>6.2</td></tr><tr><td>L2 proficiency <sup>b</sup></td><td>71.2</td><td>20.0</td><td>32-113</td><td>67.6</td><td>79.1</td></tr><tr><td colspan="6"><strong>Control group (n = 29)</strong></td></tr><tr><td>Age (years)</td><td>16.0</td><td>0.3</td><td>16-17</td><td>15.9</td><td>16.1</td></tr><tr><td>Age of onset (years)</td><td>6.1</td><td>1.6</td><td>3-10</td><td>5.5</td><td>6.7</td></tr><tr><td>L2 instruction (years)</td><td>9.9</td><td>1.6</td><td>6-13</td><td>9.2</td><td>10.4</td></tr><tr><td>L2 use (hours/week)</td><td>2.7</td><td>1.5</td><td>0-6</td><td>2.1</td><td>3.2</td></tr><tr><td>Self-estimated proficiency <sup>a</sup></td><td>5.7</td><td>1.7</td><td>1-9</td><td>5.0</td><td>6.3</td></tr><tr><td>L2 proficiency <sup>b</sup></td><td>71.7</td><td>21.2</td><td>35-116</td><td>63.3</td><td>80.1</td></tr></tbody></table>

## 2.2 Task-based intervention: Stimulus materials and procedure

Over 7 weeks, learners in the experimental group performed a sequence of 20 tasks that simulated an end-of-the-course trip to London. Tasks contained 80 consonant-vowel-consonant (CVC) words, coming from 24 minimal pairs containing the two target contrasts /i: – ɪ/ and /æ – ʌ/ as well as other words containing the four target vowels without being minimal pairs. Half of the words were monosyllabic and half were disyllabic (Appendix A). Each contrast was presented once in every task, and the stimuli consisted of six minimal pairs and eight extra words containing the target vowels. Four Southern Standard British English (SSBE) speakers recorded the aural input of the listening comprehension activity in the pre-task phase. Tasks were designed following Willis' (1996) framework for task-based learning, namely, a three-phase framework corresponding to a pre-task, task cycle, and language focus stage (see examples in Mora-Plaza, 2021; Mora-Plaza et al., 2022).

The pre-task lasted for 10 minutes. First, the teacher presented the topic area of the session through an illustration of a real-life activity (e.g., packing a suitcase) and elicited students' experiences. Relevant words and expressions were written on the whiteboard and noted down by students. Then, students listened to a conversation which replicated the task each pair was going to carry out during the task cycle. Students listened for overall comprehension, then they had to pay attention to certain words which were inserted, in order to trigger a focus on phonetic form (e.g., *cap/kæp/* and *cup/kʌp/*). Finally, the teacher showed a picture of the target object

<footnote><sup>a</sup> Averaged self-estimated ability to speak spontaneously, understand, read, write, and pronounce in English.</footnote>

<footnote><sup>b</sup> Obtained through an elicited imitation (EI) task (Ortega et al., 2002).</footnote>
on screen and elicited the word. Students had to guess the word and listen to it. The teacher set the goal of the main task and gave planning time to prepare for it.

The task cycle lasted approximately 15–20 minutes and consisted of 20 problem-solving tasks which were two-way, close, and convergent. Additionally, tasks were “designed to provide opportunities for communicating using some specific linguistic feature” (Ellis, 2009, p. 223); namely, learners had to be able to distinguish L2 vowel contrasts (/i: – ɪ/ or /æ – ʌ/) in order to perform the task successfully (i.e., task essentialness; Loschky & Bley-Vroman, 1993). The task cycle consisted of three different phases:

1. Task – Students performed the task in dyads and the teacher monitored students' performance. The teacher made sure students were using the L2 and promoted spontaneous talk and confidence building.

2. Planning – Students rehearsed the outcome of the task and organised their discourse before presenting it in front of their classmates.

3. Report – Students presented their reports of the task in front of their classmates. The teacher noted down any inaccuracies related to the target vowels, to comment on them during the language focus stage.

The language focus stage lasted for 5–10 minutes. During this stage, the teacher prepared some language-focused tasks to consolidate the phonological contrasts encountered through communication during the task cycle. In the analysis stage, students did consciousness-raising activities and, in the practice stage, they consolidated the target pronunciation features through communicative tasks.

## 2.3 Assessment

Learners' L2 phonological knowledge was assessed through perception and production tests. In this paper, we will only report the results of L2 vowel production. Learners produced the L2 target vowels through delayed word repetition (DWR) and delayed sentence repetition (DSR) tasks, which were administered in DMDX<fnref n="2" /> (Forster & Forster, 2003) on a laptop computer.

In the DWR task, participants heard the word (e.g., /kæt/) followed by a 1500ms pause, before a tone signal prompted them to repeat it. In order to test for generalisation effects, the testing stimuli comprised 24 taught and 24 untaught words, and were produced by two speakers that participants had not been exposed to during the intervention. The test consisted of a total of 68 trials (64 test and 4 practice trials). The testing stimuli were 32 monosyllabic and 32 disyllabic words: 48 were words from minimal pairs /i: – ɪ/ and /æ – ʌ/, and 16 words had no contrasting counterpart but contained the 4 target vowels and also had appeared during the intervention (Appendix B).

In the DSR task, learners were asked to: 1) read the sentence appearing in standard orthography on the computer screen for 3000ms; 2) listen to the sentence over the headphones; and 3) repeat the sentence from memory after a sound signal occurring 1500ms after the offset of the sentence stimulus. The DSR stimuli were identical to the DWR ones. Learners were exposed to 64 test sentences and four practice sentences, which were four words long. They were always formed by the determiner/pronoun THE/THEY + TARGET WORD containing /i:, ɪ, æ, ʌ/ + VERB + OBJECT (e.g., *The bin is empty*). All test words (DWR) and sentences

<footnote n="2">² DMDX (Forster & Forster, 2003) is a Win32-based software display system used in psychological and linguistic experiments for stimulus presentation (providing fast-action, dynamic gaming experience) and for measuring reaction times to visual and auditory stimuli.</footnote>
(DSR) were distributed into two separate randomised blocks (1st block /i:/, /ɪ/; 2nd block /æ/, /ʌ/) with 32 stimuli each and a short break in between.

## 2.4 Data analysis

To obtain an L2 vowel production measure, vowel frequencies were extracted in Praat. A Bark-distance normalisation procedure was used to provide speaker-independent estimates of vowel quality. The difference in Bark between F1 and f0 (B1-B0) estimated vowel height, whereas the difference between F2 and F1 (B2-B1) estimated vowel frontness.

Mahalanobis distances were used to calculate a measure of vowel distinctiveness (i.e., every token of vowel /æ/ and the centroid of the distribution of the tokens of the other contrasting vowel /ʌ/, and vice versa). A larger distance meant less of an overlap between the two vowels (Melnik-Leroy & Peperkamp, 2021).<fnref n="3" /> In addition, to measure vowel nativelikeness, we calculated the distance between native speakers' and learners' productions of each target vowel produced in the same phonetic context, so a smaller distance meant a more target-like production (Kartushina et al., 2015).

In order to answer RQ1 and RQ2, linear mixed-effects models were performed in SPSS 27 with GROUP (Experimental vs. Control), TIME (pre-test vs. post-test), CONTRAST (/i: – ɪ/ vs. /æ – ʌ/) or VOWEL (/i:, ɪ, æ, ʌ/), and their interactions as fixed effects, and SUBJECT and ITEM as random intercepts. As for RQ3, we calculated gains from pre-test to delayed post-test scores for the experimental group only. In a linear-mixed effects model, we included TOKEN TYPE (taught vs. untaught) as fixed effects and a random intercept for SUBJECT. The parameter estimates are given in Appendix C.

## 3 Results

RQ1 queried the effects of TBPT on L2 vowel production in words elicited in isolation. On the one hand, mixed effects models revealed significant main effects of TIME ($F[1, 8680] = 7.08, p = .008$) and CONTRAST ($F[1, 8680] = 9.17, p = .002$) on Mahalanobis distances between vowels /i: – ɪ/, /æ – ʌ/, i.e., distinctiveness measure. A significant GROUP × TIME interaction ($F[1, 8680] = 6.90, p = .009$) revealed that, at post-test, the experimental group significantly produced a larger distance between the vowels in the contrasts (pre-test: $M = 10.24; SD = .37$; post-test: $M = 12.96; SD = .32; p < .001$) than the control group (pre-test: $M = 10.18; SD = .61$; post-test: $M = 10.16; SD = .80; p = .984$). Bonferroni-adjusted pairwise contrasts from the GROUP × TIME × CONTRAST interaction ($F[1, 8680] = 1.16, p = .282$) showed that, while the task-based intervention seemed to have helped learners produce a larger distance between /i:/ and /ɪ/ ($t[8680] = 2.20, p = .027$), and /æ/ and /ʌ/ ($t[8680] = 5.00, p < .001$), none of the control group's contrasting vowels distinguished significantly at post-test ($p > .05$) (see Figure 2, left panel).

On the other hand, mixed effects models showed non-significant main effects of TIME ($F[1, 8672] = .17, p = .679$) and significant effects of VOWEL ($F[3, 8672] = 29.37, p < .001$) on Mahalanobis distances between learners' and native speakers' vowels /i:, ɪ, æ, ʌ/, i.e., nativelikeness measure. Despite the non-significant GROUP × TIME interaction ($F[1, 8672] = 2.59, p = .107$), Bonferroni-adjusted pairwise contrasts showed that overall the experimental group (but not the control group) had significantly shortened Mahalanobis distances compared to native speakers (i.e., the participants became more accurate) between testing times (pre-test: $M = 20.03; SD = .79$; post-test: $M = 18.26; SD = .89; p = .05$). As illustrated in Figure 2 (right

<footnote n="3">³ Mahalanobis distances are defined as the distance in standard deviations between a point and the centroid of a distribution (Melnik-Leroy & Peperkamp, 2021).</footnote>
panel), only learners' productions of /æ/ and /ʌ/ significantly approximated the values of native speakers' vowel productions. Finally, learners in the experimental group kept separating the confusing vowels in the contrasts (/i: - ɪ/ and /æ - ʌ/) as demonstrated by the vowel distinctiveness measures at the delayed post-test (post-test: *M* = 12.96, *SD* = .32; delayed post-test: *M* = 13.98, *SD* = .39; *p* = .05) and maintained similar Mahalanobis nativelikeness distances (post-test: *M* = 18.26, *SD* = .89; delayed post-test: *M* = 17.34, *SD* = .83; *p* = .47), suggesting that learning was retained 11 weeks after the treatment.

Figure 2

<figure><img src="image_63.png" /><figcaption>*Mahalanobis Distances for Distinctiveness (on the Left) and for Nativelikeness (on the Right) Produced in Words in Isolation*</figcaption></figure>

*Note.* The graphs are organised by GROUP (Experimental vs. Control) and TIME (pre-test vs. post-test) in the X-axis. Error bars show 95% CI.

RQ2 also asked about the effects of TBPT on L2 vowel production but this time in words produced in sentences. In terms of Mahalanobis distances of vowel distinctiveness, mixed effects models revealed significant main effects of TIME (*F*[1, 8680] = 21.31, *p* < .001) and CONTRAST (*F*[1, 8680] = 20.55, *p* < .001). In addition, results from the GROUP × TIME interaction (*F*[1, 8680] = 49.41, *p* < .001) indicated that the experimental group produced significantly greater distances between the confusing vowels for the two contrasts after the task-based intervention (pre-test: *M* = 8.52; *SD* = .37; post-test: *M* = 14.64; *SD* = .32; *p* < .001), whereas the control group did not make any significant distinction between any of the target vowels in the contrasts (pre-test: *M* = 8.00; *SD* = .61; post-test: *M* = 6.57; *SD* = .79; *p* = .157) (see Figure 3, left panel).

Concerning Mahalanobis nativelikeness distances, linear mixed models revealed non-significant effects of TIME (*F*[1, 8675] = .17, *p* = .241) and significant effects of VOWEL (*F*[3, 8675] = 45.20, *p* < .001). Furthermore, a significant GROUP × TIME interaction (*F*[1, 8675] = .17, *p* = .241) arose because, according to Bonferroni-adjusted pairwise contrasts, experimental learners' vowels became more target-like (i.e., the distance to native speaker
values was reduced) from pre- (M = 25.78, SD = .79) to post-test (M = 21.50, SD = .89; *p* < .001), but the control group's vowel productions did not change significantly across times (pre-test: M = 25.05, SD = .91, post-test: M = 26.23, SD = 1.37; *p* = .268). As seen in Figure 3 (right panel), learners' vowel qualities became significantly more accurate after the intervention, except for vowel /i/ (*p* = .798). Lastly, evidence for retention effects was found as learners in the experimental group still distinguished the confusing vowels in the contrasts at the delayed post-test (post-test: M = 14.64, SD = .32; delayed post-test: M = 13.75, SD = .39; *p* = .06) and did so in a native-like direction (post-test: M = 21.50, SD = .89; delayed post-test: M = 20.17, SD = .83; *p* = .29).

<caption>Figure 3</caption>

*Mahalanobis Distances for Distinctiveness (on the Left) and for Nativelikeness (on the Right) Produced in Words in Sentences*

<figure><img src="image_64.png" /></figure>

*Note.* The graphs are organised by GROUP (Experimental vs. Control) and TIME (pre-test vs. post-test) in the X-axis. Error bars show 95% CI.

Interestingly, gains in distinctiveness were moderately correlated with gains in nativelikeness when vowels were embedded in words produced in isolation (*r* = .330, *p* = .008) and in sentences (*r* = .429, *p* = .001). This suggests that, overall, learners who produced more distinct vowel qualities, also produced vowels that were more target-like.

Finally, RQ3 looked into the comparison between vowel production gains for taught and untaught tokens in two different contexts: words and sentences. On the one hand, learners obtained similar gains in taught (M = 4.06; SD = .94) and untaught (M = 3.40; SD = .78) tokens produced in isolation with regards to vowel distinctiveness (F[1, 501] = .28, *p* = .593). In contrast, gains for vowel nativelikeness were greater (albeit non-significantly; F[1, 501] = 1.11, *p* = .291) for those words that had not been taught and were unfamiliar to learners than taught tokens. Likewise, Mahalanobis distance gains between vowels produced in sentences, were similar when they appeared in taught (M = 5.55; SD = .96) and untaught (M = 4.90; SD = .79) tokens (F[1, 501] = .26, *p* = .606). Gains in how much learners approximated native speakers’
vowel qualities were larger in untaught than taught tokens, but the effects of TOKEN TYPE did not reach significance ($F[1, 499] = 1.12, p = .293$).

## 4 Discussion

Results from this investigation suggest that carefully designing and manipulating tasks induces a focus on phonetic form during meaningful interaction, and generating a linguistic focus through task-essential language raises learners' awareness about challenging L2 pronunciation features, eventually leading to more accurate vowel production (see Solon et al., 2017). Learners who took part in the task-based intervention produced L2 vowels more contrastively and more accurately than learners who did not. In word-elicitation contexts (RQ1), the overlap between confusable vowels became significantly smaller for both contrasts and L2 vowels became more target-like. Similarly, in sentence-elicitation contexts (RQ2), learners produced L2 vowels more distinctively and accurately after the task-based intervention. This was not the case for the control group, whose L2 vowel qualities remained stable. Whereas producing words in isolation may have led to more conscious reflections on form (thus emphasising the distinctiveness of vowels in terms of spectral distances), producing the target words embedded in sentences may have mirrored the occurrence of such forms during the interactive tasks, in a more realistic context, where vowel differences relied mainly on quality (Mora et al., 2022). Changes in vowel distinctiveness were significantly associated with changes in nativelikeness, meaning that TBPT helped learners align their initially unstable vowel productions with those of native speakers of English. While the goal of the TBPT intervention was not to achieve a native-like accent, approximating native vowels may have helped learners to become more intelligible, hence, to produce L2 vowels that were sufficiently distinct in order not to confuse interlocutors during communication. In addition, L2 vowel learning seems to be robust, as L2 pronunciation gains were retained 11 weeks after the intervention. Finally, as found by HVPT studies (Thomson, 2018), gains in L2 pronunciation accuracy generalised to untaught tokens in isolation, as well as to tokens embedded in sentences (RQ3) and those spoken by unfamiliar speakers/voices.

Overall, findings from this study suggest that pronunciation instruction can be easily integrated in communicative tasks (in line with current pedagogical principles) by making L2 pronunciation features salient through task manipulation (e.g., making L2 vowel contrasts essential for task completion). Instead of teaching pronunciation in an explicit, often decontextualised manner, TBPT thus advocates for an analytic approach where learners deal with challenging L2 pronunciation features as they are communicating. In line with previous form-focused communicative studies (e.g., Darcy et al., 2021), exposing learners to L2 pronunciation features repetitively and in meaningful contexts results in L2 pronunciation gains; it also prepares learners for out-of-class conversations. Hypothetically, other L2 oral skills (e.g., fluency, prosody) may also develop along with segmentals while learners interact. Finally, L2 pronunciation improvement may be assessed in terms of successful task completion as well as objective and subjective pronunciation proficiency measures.

## 5 Conclusion

This TBPT study has shown that, despite the time constraints that teachers often suffer, L2 pronunciation can be part of a TBLT curriculum. Form-focused communicative instruction, which is based on tasks that are inherently repetitive yet genuinely communicative (see Sardegna, 2022), may enhance L2 pronunciation learning and lead to generalisation effects in diverse lexical contexts and elicitation modes. Further research should investigate how many segmental features can be addressed in a given task, as well as how often learners should
practise the same minimal pairs for acquisition to occur. More broadly, future work should
explore: the effects of task design and manipulation on L2 intelligibility and comprehensibility
in face-to-face and online settings; how TBPT may apply to the teaching of suprasegmentals;
and which learner factors (experiential, affective, and/or cognitive) should be considered when
designing tasks that promote second language pronunciation learning.

Acknowledgements

This research was funded through grant PID2019-107814GB-I00 from the Spanish Ministry of Science, Innovation and Universities. I would like to thank Miren Adrian, Daniela Avello and Valeria Galimberti for their help in data collection, and Dr. Joan C. Mora and Dr. Roger Gilabert for their constant support.

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## Appendix A

Intervention Stimuli by Vowel (i:/, /i/, /æ/, /ʌ/), Type (Minimal Pairs vs. Extra Words also Containing the Target L2 Vowels) and Syllable (One- vs. Two-Syllable Words)

<table><thead><tr><th></th><th>/i:/</th><th>/ɪ/</th><th>/æ/</th><th>/ʌ/</th></tr></thead><tbody><tr><td colspan="5"><strong>Minimal pairs</strong></td></tr><tr><td rowspan="6"><strong>1 syllable</strong></td><td>bean</td><td>bin</td><td>bag</td><td>bug</td></tr><tr><td>cheek</td><td>chick</td><td>bat</td><td>butt</td></tr><tr><td>feast</td><td>fist</td><td>cap</td><td>cup</td></tr><tr><td>peel</td><td>pill</td><td>cat</td><td>cut</td></tr><tr><td>sheep</td><td>ship</td><td>mag</td><td>mug</td></tr><tr><td>teen</td><td>tin</td><td>ram</td><td>rum</td></tr><tr><td rowspan="6"><strong>2 syllables</strong></td><td>heating</td><td>hitting</td><td>amber</td><td>umber</td></tr><tr><td>keeper</td><td>kipper</td><td>ankle</td><td>uncle</td></tr><tr><td>lever</td><td>liver</td><td>babble</td><td>bubble</td></tr><tr><td>sleeper</td><td>slipper</td><td>batter</td><td>butter</td></tr><tr><td>sneakers</td><td>Snickers</td><td>carry</td><td>curry</td></tr><tr><td>weeping</td><td>whipping</td><td>natty</td><td>nutty</td></tr><tr><td colspan="5"><strong>Extra words</strong></td></tr><tr><td rowspan="4"><strong>1 syllable</strong></td><td>leave</td><td>kill</td><td>act</td><td>run</td></tr><tr><td>weed</td><td>fish</td><td>hat</td><td>drum</td></tr><tr><td>tea</td><td>chips</td><td>ham</td><td>bun</td></tr><tr><td>jeans</td><td>pin</td><td>jam</td><td>gun</td></tr><tr><td rowspan="4"><strong>2 syllables</strong></td><td>illegal</td><td>bitter</td><td>jacket</td><td>public</td></tr><tr><td>kiwi</td><td>whiskey</td><td>baggy</td><td>nugget</td></tr><tr><td>Peter</td><td>Jimmy</td><td>Patrick</td><td>Luster</td></tr><tr><td>Sheila</td><td>Lily</td><td>Cathy</td><td>Sunset</td></tr></tbody></table>

## Appendix B

Testing Stimuli by Vowel (i:/, /i/, /æ/, /ʌ/), Token Type (Taught vs. Untaught, and Practice Items) and Syllable (One- vs. Two-Syllable Words)

<table><thead><tr><th></th><th>/i:/</th><th>/ɪ/</th><th>/æ/</th><th>/ʌ/</th></tr></thead><tbody><tr><td colspan="5"><strong>Taught</strong></td></tr><tr><td rowspan="6"><strong>1 syllable</strong></td><td>bean</td><td>bin</td><td>bag</td><td>bug</td></tr><tr><td>cheek</td><td>chick</td><td>cat</td><td>cut</td></tr><tr><td>sheep</td><td>ship</td><td>ram</td><td>rum</td></tr><tr><td>leave</td><td>fish</td><td>hat</td><td>drum</td></tr><tr><td>tea</td><td>chips</td><td>jam</td><td>bun</td></tr><tr><td>keeper</td><td>kipper</td><td>amber</td><td>umber</td></tr><tr><td rowspan="4"><strong>2 syllables</strong></td><td>lever</td><td>liver</td><td>batter</td><td>butter</td></tr><tr><td>sneakers</td><td>Snickers</td><td>carry</td><td>curry</td></tr><tr><td>illegal</td><td>bitter</td><td>jacket</td><td>public</td></tr></tbody></table>
Mora-Plaza
Task-based pronunciation teaching

<table><thead><tr><th></th><th>/i:/</th><th>/ɪ/</th><th>/æ/</th><th>/ʌ/</th></tr></thead><tbody><tr><td></td><td>kiwi</td><td>whiskey</td><td>baggy</td><td>nugget</td></tr><tr><td><strong>Untaught</strong></td><td></td><td></td><td></td><td></td></tr><tr><td><em>1 syllable</em></td><td>beef<br>feel<br>seal</td><td>biff<br>fill<br>sill</td><td>crash<br>lag<br>stab</td><td>crush<br>lug<br>stub</td></tr><tr><td><em>2 syllables</em></td><td>greeting<br>litre<br>weaner</td><td>gritting<br>litter<br>winner</td><td>attar<br>bagger<br>clatter</td><td>utter<br>bugger<br>clutter</td></tr><tr><td><strong>Practice items</strong></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>feet</td><td>hill</td><td>rat</td><td>sun</td></tr></tbody></table>

Appendix C

*Parameter estimates of linear mixed-effects models for the measures of distinctiveness and of nativelikeness*

RQ1: Words in Isolation

<table><thead><tr><th></th><th>β</th><th>SE</th><th>t</th><th>Sig.</th><th colspan="2">95% CI</th></tr><tr><th></th><th></th><th></th><th></th><th></th><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>13.633</td><td>1.1654</td><td>11.698</td><td>0.000</td><td>11.348</td><td>15.917</td></tr><tr><td>Group</td><td>-0.858</td><td>1.4082</td><td>-0.609</td><td>0.542</td><td>-3.619</td><td>1.902</td></tr><tr><td>Time</td><td>-2.157</td><td>1.2021</td><td>-1.795</td><td>0.073</td><td>-4.514</td><td>0.199</td></tr><tr><td>Contrast</td><td>-6.838</td><td>1.1556</td><td>-5.917</td><td>0.000</td><td>-9.103</td><td>-4.573</td></tr><tr><td>Group x Time</td><td>-1.741</td><td>1.4328</td><td>-1.215</td><td>0.224</td><td>-4.550</td><td>1.068</td></tr><tr><td>Group x Time x Contrast</td><td>-2.102</td><td>1.9523</td><td>-1.077</td><td>0.282</td><td>-5.929</td><td>1.725</td></tr></tbody></table>

<table><thead><tr><th></th><th>β</th><th>SE</th><th>t</th><th>Sig.</th><th colspan="2">95% CI</th></tr><tr><th></th><th></th><th></th><th></th><th></th><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>24.079</td><td>3.1393</td><td>7.670</td><td>0.000</td><td>17.925</td><td>30.232</td></tr><tr><td>Group</td><td>-17.648</td><td>3.7929</td><td>-4.653</td><td>0.000</td><td>-25.082</td><td>-10.213</td></tr><tr><td>Time</td><td>-8.243</td><td>3.4130</td><td>-2.415</td><td>0.016</td><td>-14.934</td><td>-1.553</td></tr><tr><td>Vowel</td><td>-4.969</td><td>3.3487</td><td>-1.484</td><td>0.138</td><td>-11.533</td><td>1.595</td></tr><tr><td>Group x Time</td><td>12.267</td><td>4.0817</td><td>3.005</td><td>0.003</td><td>4.265</td><td>20.268</td></tr><tr><td>Group x Time x Vowel</td><td>-11.446</td><td>5.6656</td><td>-2.020</td><td>0.043</td><td>-22.552</td><td>-0.340</td></tr></tbody></table>
## RQ2: Sentences

<table><thead><tr><th rowspan="2"></th><th rowspan="2">β</th><th rowspan="2">SE</th><th rowspan="2">t</th><th rowspan="2">Sig.</th><th colspan="2">95% CI</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>15.810</td><td>1.9139</td><td>8.261</td><td>0.000</td><td>12.059</td><td>19.562</td></tr><tr><td>Group</td><td>1.978</td><td>2.3216</td><td>0.852</td><td>0.394</td><td>-2.573</td><td>6.529</td></tr><tr><td>Time</td><td>0.527</td><td>1.2041</td><td>0.437</td><td>0.662</td><td>-1.834</td><td>2.887</td></tr><tr><td>Contrast</td><td>-6.830</td><td>1.1772</td><td>-5.802</td><td>0.000</td><td>-9.137</td><td>-4.522</td></tr><tr><td>Group x Time</td><td>-6.187</td><td>1.4285</td><td>-4.331</td><td>0.000</td><td>-8.987</td><td>-3.387</td></tr><tr><td>Group x Time x Contrast</td><td>-2.564</td><td>1.9207</td><td>-1.335</td><td>0.182</td><td>-6.329</td><td>1.201</td></tr></tbody></table>

<table><thead><tr><th rowspan="2"></th><th rowspan="2">β</th><th rowspan="2">SE</th><th rowspan="2">t</th><th rowspan="2">Sig.</th><th colspan="2">95% CI</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>21.844</td><td>3.1414</td><td>6.953</td><td>0.000</td><td>15.686</td><td>28.002</td></tr><tr><td>Group</td><td>-12.259</td><td>3.7954</td><td>-3.230</td><td>0.001</td><td>-19.698</td><td>-4.819</td></tr><tr><td>Time</td><td>-0.259</td><td>3.4145</td><td>-0.076</td><td>0.939</td><td>-6.953</td><td>6.434</td></tr><tr><td>Vowel</td><td>5.016</td><td>3.3501</td><td>1.497</td><td>0.134</td><td>-1.551</td><td>11.583</td></tr><tr><td>Group x Time</td><td>6.804</td><td>4.0835</td><td>1.666</td><td>0.096</td><td>-1.201</td><td>14.808</td></tr><tr><td>Group x Time x Vowel</td><td>-0.905</td><td>5.6680</td><td>-0.160</td><td>0.873</td><td>-12.016</td><td>10.205</td></tr></tbody></table>

## RQ3: Words in Isolation

<table><thead><tr><th rowspan="2"></th><th rowspan="2">β</th><th rowspan="2">SE</th><th rowspan="2">df</th><th rowspan="2">t</th><th rowspan="2">Sig.</th><th colspan="2">95% CI</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>3.566313</td><td>1.064224</td><td>501</td><td>3.351</td><td>0.001</td><td>1.475421</td><td>5.657205</td></tr><tr><td>Token Type</td><td>0.657299</td><td>1.228860</td><td>501</td><td>0.535</td><td>0.593</td><td>-1.757055</td><td>3.071653</td></tr><tr><td>Contrast</td><td>-0.320170</td><td>1.228860</td><td>501</td><td>-0.261</td><td>0.795</td><td>-2.734525</td><td>2.094184</td></tr></tbody></table>

<table><thead><tr><th rowspan="2"></th><th rowspan="2">β</th><th rowspan="2">SE</th><th rowspan="2">df</th><th rowspan="2">t</th><th rowspan="2">Sig.</th><th colspan="2">95% CI</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>5.244276</td><td>4.671135</td><td>499</td><td>1.123</td><td>0.262</td><td>-3.933241</td><td>14.421792</td></tr><tr><td>Token Type</td><td>-4.414901</td><td>4.177990</td><td>499</td><td>-1.057</td><td>0.291</td><td>-12.623522</td><td>3.793720</td></tr><tr><td>Vowel</td><td>-1.363169</td><td>5.908571</td><td>499</td><td>-0.231</td><td>0.818</td><td>-12.971912</td><td>10.245573</td></tr></tbody></table>

## RQ3: Sentences

<table><thead><tr><th rowspan="2"></th><th rowspan="2">β</th><th rowspan="2">SE</th><th rowspan="2">df</th><th rowspan="2">t</th><th rowspan="2">Sig.</th><th colspan="2">95% CI</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>4.307979</td><td>1.083649</td><td>501</td><td>3.975</td><td>0.000</td><td>2.178924</td><td>6.437035</td></tr><tr><td>Token Type</td><td>0.645394</td><td>1.251290</td><td>501</td><td>0.516</td><td>0.606</td><td>-1.813027</td><td>3.103816</td></tr><tr><td>Contrast</td><td>1.198348</td><td>1.251290</td><td>501</td><td>0.958</td><td>0.339</td><td>-1.260073</td><td>3.656770</td></tr></tbody></table>

<table><thead><tr><th rowspan="2"></th><th rowspan="2">β</th><th rowspan="2">SE</th><th rowspan="2">df</th><th rowspan="2">t</th><th rowspan="2">Sig.</th><th colspan="2">95% CI</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>Intercept</td><td>8.799831</td><td>4.684930</td><td>499</td><td>1.878</td><td>0.061</td><td>-0.404789</td><td>18.004451</td></tr><tr><td>Token Type</td><td>-4.414901</td><td>4.190329</td><td>499</td><td>-1.054</td><td>0.293</td><td>-12.647763</td><td>3.817961</td></tr><tr><td>Vowel</td><td>-1.363169</td><td>5.926020</td><td>499</td><td>-0.230</td><td>0.818</td><td>-13.006195</td><td>10.279856</td></tr></tbody></table>
## About the author

**Ingrid Mora-Plaza** is a Lecturer in the Department of Modern Languages and Literatures and English Studies at the University of Barcelona, Spain, where she teaches English phonetics and phonology courses. She is part of the Barcelona L2 speech research group and GRAL research group on the acquisition of languages. Her research focuses on L2 pronunciation learning and teaching in foreign language contexts and the effects of individual differences on L2 speech acquisition. She is especially interested in the potential benefits of task-based pronunciation teaching and high-variability phonetic training on L2 speech development in instructional settings.

E-mail: imoraplaza@ub.edu
# Effects of silent letters on the L2 English pronunciation of L1 French learners

Marine Mouquet

Aix Marseille University

Paolo Mairano

University of Lille

This paper investigates the effects of orthography on second language (L2) phonology. We replicate a study by Bassetti and Atkinson (2015) investigating the intrusion of silent consonants in production; while the original study was conducted on L1 Italian learners of L2 English, we focus on L1 French learners of L2 English. We recruited 110 French undergraduate students specialising in English in various French universities and we ran two tests to elicit the production of 7x2 target words containing silent letters. In the first task (reading aloud task) participants saw the spelling of target words, while in the second task (word repetition task), participants initially saw their spelling, but then the spelling vanished before beginning the production. The results show that: 1) participants were significantly affected by spelling in both tasks and produced a high proportion of intrusive consonants prompted by silent letters; and 2) when orthographic input was present, more intrusive consonants corresponding to silent letters were produced. These results extend the findings of the original study on Italian participants to French participants. Furthermore, since French (contrary to Italian) has a relatively opaque spelling system, these results suggest that silent letters can have an effect on L2 pronunciation not only for learners with a transparent L1 orthographic system, but also for those who have an opaque L1 orthographic system.

**Keywords:** L2 phonology, orthography, silent letters, speech production, second language acquisition

<figure><img src="image_65.png" /></figure>
# 1 Background

Research in second language (L2) phonology has long focused on the cross-linguistic influence of the native language (L1) on the L2. Among the numerous models formulated to explain the difficulties faced by L2 learners in acquiring L2 phonology through their L1 phonological systems, the most influential are The Perceptual Assimilation Model (Best, 1994) and the Speech Learning Model (Flege, 1995). However, when an L2 is acquired via instructed learning, the acquisition process is achieved not only via spoken input, but also and often mainly via written input (as opposed to L1s, which are acquired through spoken input). It is therefore understandable that many recent studies have turned to the effects of orthography on L2 production and perception.

Research has found that orthography can either be a facilitating or a misleading factor in second language pronunciation, especially at the early stages of language acquisition. Among the beneficial effects of orthography, it has been demonstrated that providing orthographic input to L2 learners enhances the memorisation and retrieval of vocabulary (Bürki et al., 2019) and assists L2 learners in perceiving and distinguishing L2 sounds (Escudero et al., 2008; Escudero et al., 2014). In contrast, among the undesirable effects of orthography, researchers have shown that orthography can negatively affect L2 phonological representations, resulting in non-target-like productions (Bürki et al., 2019), notably segmental additions, omissions and substitutions (Bassetti, 2008). This can even lead to a phonological category from the L1 being imported; notably, Bassetti et al. (2018) reveal that Italian learners produce a singleton-geminate contrast in English reflecting spelling, e.g., *finish* vs. *Finnish*.

L2 learning may vary according to different factors, and the degree of transparency of the orthographic system in the L1 and the L2 is one of them. The orthographic system of some languages can be considered transparent: for instance, Finnish, Dutch, and Italian are acknowledged to have transparent orthographic systems, characterised mostly by one-to-one grapheme-phoneme and phoneme-grapheme correspondences (Aro, 2013). On the contrary, the orthographic systems of English, Irish, and French are considered to be opaque (or deep) since they often deviate from such correspondences (Erdener & Burnham, 2005). Therefore, it seems reasonable to claim that the phonological patterns of L2 languages with a transparent orthography can be easier to predict, because orthographic input can give direct information about the pronunciation of words (Seymour et al., 2003). Furthermore, researchers have suggested that learners whose L1 has a transparent orthographic system may tend to rely more heavily on orthography than learners whose L1 has an opaque orthographic system (Erdener & Burnham, 2005). Clearly, this may then be problematical for learners whose L1 has a transparent orthographic system targeting an L2 with an opaque orthographic system. For instance, Bassetti and Atkinson (2015) investigated the effects of silent letters (i.e., orthographic cues that are never produced) in reading aloud and word repetition tasks, revealing that L1 Italian learners of L2 English tended to pronounce intrusive consonants for silent letters, and more so when orthographic input was directly displayed.

In this study, we sought to replicate the two tests carried out by Bassetti and Atkinson (2015) originally on Italian learners, by running similar tasks with L1 French learners of L2 English. Contrary to Italian, the orthographic system of French is opaque and includes many one-to-many and many-to-one correspondences, including many cases of silent letters. This may lead us to expect, based on Erdener and Burnham (2005), that French learners of English may have fewer issues with silent letters in English than Italian learners: since their L1 orthographic system is less transparent and includes silent letters, L1 French learners may rely less than L1 Italian learners on orthography to predict phonological patterns of the L2. However, this prediction contradicts the experience of many teachers of English in France, who regularly witness the challenges posed by silent letters to French learners. Moreover, the impact of such
letters on production is not well-documented. Thus, our study not only replicates the original one, but extends it to a different population (L1 French learners), thereby providing a testbed for the claims of Erdener and Burnham (2005).

# 2 Research methodology

## 2.1 Research questions and hypotheses

The study aims to investigate the following research questions:

**RQ1:** To which degrees will French learners be affected by silent letters resulting in additional segmental units in their output?

**RQ2:** Do learner variables: a) living abroad and length of stay abroad; b) onset of English acquisition; c) L2 proficiency level; and d) variety comprehension, interact with orthographic effects?

We hypothesise that even though there are many silent letters in French, orthographic forms will still affect French learners' pronunciation of silent letters in English. Following Bassetti and Atkinson (2015), orthographic input is provided in the reading aloud task, but only partially in the word repetition task (i.e., orthographic input is provided briefly but vanishes as soon as the audio starts playing). Thus, we predict that more intrusive consonants will be produced for silent letters in the former task than in the latter. Following Erdener and Burnham (2005), we predict that French learners will be misled by silent letters to a lesser extent than Italian learners, since French is orthographically less transparent than Italian and includes many silent letters.

We also expect some learner variables, such as L2 proficiency, to counterbalance those effects. For instance, second-year undergraduate students at the English Department, University of Lille, are given lectures on grapho-phonemic rules and particularly on silent letters as part of their course in English phonetics in the first semester. In order to evaluate the impact of such lectures, the current study compares the production of first-year vs. second-year and third-year students. It is predicted that second-year students will produce fewer silent letters than the two other groups. This expectation arises from the fact that first-year students have not received any instructions on silent letters and that second-year students have more recently received lectures on silent letters than third-year students. Therefore, third-year students are also expected to produce fewer silent letters than first-year students.

## 2.2 Participants, task stimuli, and experiment procedure

Due to the COVID-19 lockdown, the two tests were hosted on a website, run remotely, and conducted via computers, without being available on smartphones. Therefore, unlike Bassetti and Atkinson (2015), participants used their own equipment. They were advised to perform the experiment in a quiet room and to use headphones for the repetition task. The website was coded in Javascript/JQuery for the dynamic part and in HTLM/CSS for the static part. More precisely, the website also used Boostrap for the layout. For the recordings, we used the library Recorder.js, published under the MIT licence by Matt Diamond. All the recordings and data were gathered on a MySQL database thanks to PHP.

The tasks were completed by 110 L1 French participants of L2 English with no reported language or reading impairments: 38 first-year, 24 second-year and 48 third-year students. All of them were undergraduate students specialising in English in various French universities (F = 92, M = 18, a typical gender bias among students in language departments in France). The
median self-reported level of English was B2 and ranged from B1 to C2. Twenty respondents had lived in an English-speaking country (mainly the UK and the US but also Canada, South Africa, Singapore, and New Zealand) with an average duration of 20 months (MD = 10.5, SD = 18.77). Participation was voluntary and unpaid.

Written instructions were given in French before each task. All participants were exposed to 37 stimuli appearing in the same order determined randomly for both tasks (see Table 1): seven target words included the silent letters <b>, <d>, and <l> in different positions, which were the focus of our analysis; 24 fillers (homophones<fnref n="1" />); three words including optionally silent letters<fnref n="2" />; and three filler words. The word *landscape* was included in the list of target words in Bassetti and Atkinson (2015) but it was discarded from our study because the silent <d> is frequently produced by native speakers<fnref n="3" />.

<caption>**Table 1**</caption>

*Stimuli Words*

<table><thead><tr><th>Target words</th><th>Homophones</th><th>Words with optional silent letters</th><th>Filler words</th></tr></thead><tbody><tr><td>climb</td><td>aloud</td><td>allowed</td><td>sandwich</td></tr><tr><td>comb</td><td>caught</td><td>court</td><td>grandson</td></tr><tr><td>debt</td><td>flour</td><td>flower</td><td>landscape</td></tr><tr><td>lamb</td><td>higher</td><td>hire</td><td></td></tr><tr><td>Wednesday</td><td>one</td><td>won</td><td></td></tr><tr><td>salmon</td><td>principal</td><td>principle</td><td></td></tr><tr><td>walk</td><td>right</td><td>write</td><td></td></tr><tr><td></td><td>sauce</td><td>source</td><td></td></tr><tr><td></td><td>seas</td><td>seize</td><td></td></tr><tr><td></td><td>son</td><td>sun</td><td></td></tr><tr><td></td><td>which</td><td>witch</td><td></td></tr><tr><td></td><td>wood</td><td>would</td><td></td></tr></tbody></table>

Homophones were notably included in the stimuli because Bassetti and Atkinson (2015) include four different studies investigating several aspects of orthographic effects. We did not test orthographic effects on the pronunciation of homophones. However, the same stimuli were used in order to: 1) do a valid replication and be able to compare results, and 2) to distract participants from silent letters with different fillers. Stimuli were sorted randomly and presented to participants, although it was impossible to apply the exact same order as this information was not provided in Bassetti and Atkinson (2015).

In the first task, each word appeared on the screen and participants had to click to start recording, and then read the written word aloud within a timeframe of three seconds. No acoustic input was provided in this task. As the experiment was conducted at home and not in a supervised laboratory environment, the test screen displayed a ‘Retry’ button, in case

<footnote n="1">¹ The homophones were used for a different study by Bassetti and Atkinson (2015).</footnote>

<footnote n="2">² These words have letters that are claimed to be pronounced by British English natives and were therefore discarded from the analysis (see Bassetti & Atkinson, 2015).</footnote>

<footnote n="3">³ As already shown with *sandwich* and *grandson* in Bassetti and Atkinson (2015).</footnote>
participants encountered recording issues or other technical problems. However, participants were encouraged to be spontaneous and record each word just once. Only the last version was kept for the analysis. A bar at the top tracked their progress for each task. Once they had recorded the 37 words, they could move on to the second task.

In the word repetition task, participants had to repeat words on the basis of a recording. The orthographic version of each word was initially shown on the screen, but vanished when participants listened to the audio. Only one listening was possible. The audio was extracted from the Cambridge Dictionary<fnref n="4" /> (online version) and was based on Southern British English (SBE). As in the previous task, participants had to record themselves repeating the target stimuli. Participants were advised to record themselves just once, but they could retry if they encountered any technical issues.

## 3 Data analysis and results

The recordings containing the seven target words were examined in isolation for each student twice (once for each task). Based on an auditory and spectrographic analysis with Praat (Boersma & Weenink, 2019), each target silent letter was coded by the authors as intrusive or non-intrusive. A sample of the recordings is presented in Figure 1.

<caption>Figure 1</caption>

*Spectrogram Analysis of the Word ‘Salmon’ with a Pronounced /l/ by a First-year Participant*

<figure><img src="image_66.png" /></figure>

In general, the results show that on average 47% of the target words were produced with an added phone during the reading aloud task vs. 24% during the word repetition task. A paired t-test assuming unequal variances confirmed that there were significantly more cases of added silent consonants in the reading aloud task than in the word repetition task ((t (209) = 7.25, p < .001; M<sub>RAT</sub> = 3.27 vs. M<sub>WRT</sub> = 1.7), thus suggesting that acoustic input reduces the intrusion of silent letters.

<footnote n="4">⁴ Cambridge Dictionary https://dictionary.cambridge.org</footnote>
Figure 2

*Proportion of Pronounced Silent Letters in Target Words: Reading Aloud Task vs. Word Repetition Task*

<figure><img src="image_67.png" /></figure>

*Note.* Data is presented in percentage and classified by significance

More detailed results of the tasks for each word are indicated in Figure 2. The `<l>` in the word *salmon* was the most problematic for French participants in both tasks: they produced 81% of `<l>` occurrences in the reading aloud task vs. 50% in the word repetition task. In addition, French participants encountered overall difficulties with the `<b>` in final position in *comb*, *lamb*, and *climb* and in middle position in *debt* (55% of the participants produced them in the word reading task vs. 26% in the word repetition task). Conversely, participants did not seem to face many difficulties with the silent `<d>` in *Wednesday* as only 8% of them pronounced it during the first task and none of them did during the second one. Most students who produced a /d/ also mispronounced other phonemes and/or stress (e.g., pronouncing it as */wed'nesdei/ and */wed'nezdei/).

In addition, written and spoken frequencies were extracted from the British National Corpus (see Table 2). In order to determine whether spoken and written lexical frequencies affected the percentage of intrusive consonants corresponding to silent letters, we examined their correlation (see Figure 3).
<caption>**Table 2**</caption>

*Occurrences of Written and Spoken Target Words in the British National Corpus (in Lemma, per Mil)*

<table><thead><tr><td>Words</td><td>Written frequency</td><td>Spoken frequency</td></tr></thead><tbody><tr><td>walk</td><td>83.59</td><td>160.88</td></tr><tr><td>Wednesday</td><td>32.54</td><td>97.76</td></tr><tr><td>debt</td><td>49.64</td><td>17.97</td></tr><tr><td>climb</td><td>20.16</td><td>10.54</td></tr><tr><td>lamb</td><td>14.8</td><td>12.95</td></tr><tr><td>salmon</td><td>13.11</td><td>9.23</td></tr><tr><td>comb</td><td>3.62</td><td>3.61</td></tr></tbody></table>

*Note.* Data retrieved from the British National Corpus in May 2021 (Davies, 2004)

<caption>**Figure 3**</caption>

*Number of Pronounced Silent Letters in the Reading Aloud Task: Spoken-to-written Frequency*

<figure><img src="image_68.png" /></figure>

Words with lower frequencies were more challenging for participants. A Spearman correlation test was used to check the distribution between the number of intrusive silent consonants for each word and its spoken and written frequencies. The correlation yielded significant results for both spoken (r = -0.89, p = 0.012) and written (r = -0.86, p = 0.024) frequencies. Spoken frequency correlates even more significantly than the written one; this is of course expected, as it is reasonable to assume that the pronunciation of words more
frequently encountered in speech is better known to learners. However, more samples are
needed to confirm the validity of this finding, as only seven words were involved in this task.

Additionally, no significant correlation was found between orthographic effects and learner-
level variables: living abroad and length of stay abroad, onset of English acquisition,
proficiency level in English, and English variety comprehension. Surprisingly, a t-test
assuming unequal variance revealed that second-year and third-year participants from the
English Department in Lille (who had received grapho-phonemic lectures on silent letters (n =
16)) did not significantly diverge from first-year participants (n = 11) from the same
Department (t (25) = 1.76; p = 0.09; M<sub>FIRST</sub> = 4.45 vs. M<sub>MOTHERS</sub> = 3.25) for the reading aloud
task and (t (20) = -0.08; p = 0.9; M<sub>FIRST</sub> = 2.27 vs. M<sub>MOTHERS</sub> = 2.31) for the word repetition task.
This may suggest that lectures on grapho-phonemic rules were not only ineffective, but also
that there does not seem to be a change from the first year to the second and third year in terms
of pronunciation of silent letters.

4 Discussion

In line with Bassetti and Atkinson's (2015) study, these findings confirm the significant effects
of orthography on L2 production: French participants produced intrusive consonants
corresponding to silent letters in 47% of words with silent letters in the reading aloud task and
24% in the word repetition task. The effects that we found for French learners of L2 English
are smaller than those found by Bassetti and Atkinson (2015) for Italian participants. This result
seems to support Erdener and Burnham's (2005) claim that the transparency of L1 orthography
has an effect on the extent to which learners rely on spelling to predict pronunciation patterns
in an L2. However, this interpretation should be tempered, because comparisons of L2 learners
from different L1s may be misleading, and many factors may influence these findings, e.g., our
French participants had less L2 instruction than the Italian participants in the original study,
having had on average, 10 years vs. 11 years. However, French participants were older and
were university students learning English, thus frequently speaking, listening, and writing
English for a minimum of 20 hours per week, whereas Italian participants in the original study
were high-school students from Rome. In addition, although French participants' self-reported
proficiency levels were examined, we did not include a control group with experienced learners
who did not receive lectures on grapho-phonemic rules. It may be that more experience with
the L2 could lower orthographic effects.

Nonetheless, beyond differences potentially due to the L1 and other factors, the difference
in results between the two tasks remains significant: when provided with orthography,
participants were decoding graphemes, and therefore the effects of spelling were more
noticeable. Yet, when investigating L2 transfer, phonological models such as PAM (Best,
1994) and SLM (Flege, 1995) do not account for orthographic effects, suggesting that more
research is needed to attempt to capture learners' difficulties in acquiring a second language.

The impact of cognates was also investigated. In the original study, Italian learners did not
encounter any difficulties with the cognate word *salmon* (in Italian *salmone*) even though the
<|> is produced in the L1. Conversely, the French *saumon* does not include any <|> but *salmon*
was the word with which French learners struggled most (i.e., 80% of them produced an
intrusive consonant corresponding to silent letters in the reading aloud task and 50% in the
word repetition task). This suggests that cognate words did not have any evident effects on the
production of intrusive consonants prompted by silent letters, confirming Bassetti and
Atkinson's (2015) findings.

The present study also yielded some unexpected results. The final <-mb> cluster (with silent
<b>) seems to be challenging for French learners of L2 English, resulting in /mb/ realisations
in 52% of the cases in the reading aloud task and 30% in the word repetition task. Yet, this