# Bridging the Communication Gap: Pragmatics and Interactional Dynamics in Deaf and Hard of Hearing Children

Chiara Mazzocconi, Céline Hidalgo, Charlie Hallart, Stéphane Roman, Roxane Bertrand, Leonardo Lancia, Daniele Schön

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Chiara Mazzocconi, Céline Hidalgo, Charlie Hallart, Stéphane Roman, Roxane Bertrand, et al. Bridging the Communication Gap: Pragmatics and Interactional Dynamics in Deaf and Hard of Hearing Children. Journal of Speech, Language, and Hearing Research, inPress. hal-05307513

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<figure><img src="image_1.png" /></figure>
Bridging the Communication Gap: Pragmatics and

Interactional Dynamics in Deaf and Hard of Hearing

Children

Chiara Mazzocconi¹,²,⁴, Céline Hidalgo¹,², Charlie Hallart⁵, Stéphane Roman¹,³, Roxane Bertrand²,⁴,
Leonardo Lancia²,⁴, Daniele Schön¹,²

¹ Aix-Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France.

² Aix-Marseille Univ, Institute of Language, Communication and the Brain, France.

³ APHM, Hôpital de la Timone, Service ORL Pédiatrique, Marseille, France.

⁴ Aix-Marseille Univ, CNRS, Laboratoire Parole et Langage, Aix-en-Provence, France.

⁵ Aix-Marseille Univ, Ecole d'Orthophonie, Marseille, France.

**Corresponding Author**: Chiara Mazzocconi, chiara.mazzocconi@univ-amu.fr; chiara.mazzocconi@live.it

**Conflict of Interest Statement:** The authors declare no conflicts of interest.
28 Abstract

29 **Purpose**: Children who are deaf and hard of hearing (DHH) often face challenges in everyday social communication, 30 even when they achieve good auditory recovery through hearing technologies. These difficulties, particularly in 31 pragmatic and interactional domains, can affect peer relationships, educational outcomes, and quality of life. This 32 study aims to characterize interactional and discourse-level challenges in DHH children with functional auditory 33 access to inform targeted interventions.

34 **Method**: We analysed dyadic child-adult interactions involving 9 DHH and 13 typically hearing (TH) children (ages 35 6–11), all using oral language. The DHH group included users of bilateral cochlear implants (CI), bimodal devices (CI 36 + hearing aid), and bilateral hearing aids. Each child interacted with an adult in a referential (treasure-hunting) task, 37 alternated with child-led subtasks (e.g., storytelling). We adopted a multilevel analysis approach ranging from 38 acoustics to pragmatics: acoustic features, turn-taking, laughter and their convergence, and dialogue acts.

39 **Results**: Turn-taking and acoustic alignment (F0, intensity, syllable rate) were similar across groups. However, dyads 40 involving DHH children are less likely to complete the task, and DHH children produce significantly shorter turns and 41 less speech-laughter. They also showed significantly lower contingent responding to adult laughter and dialogue acts.
42 Conversations with DHH children were more asymmetrical, with the adult speaking more, producing significantly 43 longer turns, less laughter and less laughter mimicry than when interacting with TH children.

44 **Conclusion**: We provide a detailed, multi-level characterization of DHH conversational dynamics while interacting 45 with a TH adult—whose behaviour at times reduces interactional opportunities for the child. These findings highlight 46 the dynamic nature of conversation and the importance of interventions that foster contingency, engagement, and 47 mutual responsiveness to support DHH children's communicative development.

48

49 Keywords: Deaf and Hard of Hearing children; Alignment; Pragmatics
50 1 Introduction

51 Technological advancements in cochlear implants and hearing prostheses have enabled children with congenital
52 hearing impairment to achieve significant auditory recovery and improve spoken language outcomes (Cejas et al.,
53 2023; Corbett & Van Zalk, 2025; Tamati et al., 2022). However, spoken language development remains highly
54 heterogeneous, with many children experiencing difficulties across various aspects of communication in
55 conversational contexts. Traditionally, assessments of spoken language development in congenitally deaf and hard of
56 hearing children with cochlear implants or hearing prostheses have focused on speech perception, phonology,
57 vocabulary, and syntax (e.g. Caselli et al., 2012; Lund, 2016; Moeller et al., 2007). However, in recent years,
58 increasing attention has been given to pragmatic aspects of communication (Paul et al., 2020). This shift is driven by
59 the recognition that pragmatic difficulties often persist despite strong phonological, vocabulary, and syntactic skills
60 (Crowe & Dammeyer, 2021; Hilviu et al., 2021; Matthews & Kelly, 2022; Most et al., 2010; Nicholas & Geers, 2006;
61 Paatsch & Toe, 2016; Parola et al., 2024; Paul et al., 2020; Rinaldi et al., 2013; Socher et al., 2019; Tobey et al.,
62 2013). Moreover, challenges in pragmatic communication have significant long-term consequences, as they are
63 negatively correlated with quality of life and peer relationships (Cummings, 2011; Haukedal et al., 2022) and
64 positively associated with emotional and mental health difficulties (Helland et al., 2014; Holzinger & Fellinger, 2022).
65 Pragmatics encompasses the rules and conventions that govern language use in context (Bara, 2010; Levinson, 1983;
66 Morris, 1938), from adaptation to the interlocutor, to the use of less-probable meaning (irony, metaphors, hyperboles).
67 Essentially, pragmatics serves as the "social grammar" of language, allowing individuals to apply their linguistic
68 knowledge effectively in conversations (Bara, 2010; Domaneschi & Bambini, 2020; Ninio & Snow, 2018; Rollins,
69 2017). Without pragmatic competence, conversational abilities are likely to be impaired, leading to difficulties in
70 initiating, maintaining, and repairing communication in social interactions (Alduais et al., 2022; Cummings, 2017,
71 2020, 2023; Norbury & Bishop, 2002).

72 Previous research has sought to characterize the communicative difficulties faced by DHH children using standardized
73 assessments and conversational analyses, examining aspects such as dialogue acts, referential explicitness,
74 contingency, adjacency and topic shifts (Paul et al., 2020)<fnref n="1" />. Although some findings have been inconsistent—likely
75 due to small sample sizes, methodological differences, variations in age at implantation, and hearing loss severity—
76 most studies report significant differences in the pragmatic domain, even when phonological, syntactic, and lexical

<footnote n="1">¹ The term conversational *contingency* refers to the degree to which an utterance is appropriately and meaningfully connected to the preceding discourse. The term *adjacency* is used to describe the expected sequencing of paired conversational turns, such as question–answer or greeting–greeting exchanges.</footnote>
77 skills are age-appropriate (Crowe & Dammeyer, 2021; Hilviu et al., 2021; Matthews & Kelly, 2022; Most et al., 2010). The variability in pragmatic performance of DHH children among studies may also stem from differences in 78 measurement approaches, which range from parental questionnaires (Bat-Chava & Deignan, 2001; Guerzoni et al., 2016; Haukedal et al., 2022; Rinaldi et al., 2013; Socher et al., 2019), theory of mind tests (Peterson, 2020), 80 standardized protocols assessing prosody, emotion recognition, and non-literal language comprehension (Hilviu et al., 2021; Parola et al., 2024), as well as conversational analyses conducted in structured and spontaneous interactions 81 with adults, therapists, or peers (Church et al., 2017; Guerzoni et al., 2016; Socher et al., 2019; Toe & Paatsch, 2013). 82 83 (For a more extensive and schematic review see Table 3A in Appendix).

85 In the present study, we aimed to build upon previous research by comparing conversational dynamics of DHH and 86 typical-hearing (TH) children in interactions with adults within pragmatically complex contexts, taking into account 87 child behaviour, adult behaviour, and their reciprocal responsivity. We employed a multilevel analytical approach 88 encompassing acoustic features (F0, intensity, speech rate), turn-taking dynamics (balance, duration, gaps, overlaps), 89 occurrences of laughter and speech-laughter, laughter responsiveness, and dialogue acts. Additionally, we examined 90 patterns of alignment, namely adjusting or converging to the partner speech, in terms of acoustic features, non-speech 91 vocalizations, turn-taking, and dialogue act contingency. This comprehensive approach was driven by the recognition 92 that conversational dynamics rely on the coordinated interaction of multiple components underpinning effective 93 communication, and by the objective of pinpointing where, within this interplay, atypicalities arise in the interactions 94 of DHH children.

95

# 1.1 Conversation and Pragmatics in Deaf and Hard of Hearing Children

97 A growing body of research has examined the pragmatic and conversational challenges faced by DHH children using 98 both standardized assessments and conversational analysis. These studies highlight specific vulnerabilities in turn- 99 taking, maintaining conversation and repair strategies (Church et al., 2017; Most et al., 2010; Paatsch & Toe, 2014; 100 Toe & Paatsch, 2013). Notably, they exhibit weaknesses in conversational contingency, the ability to process a 101 partner's turn and respond appropriately, leading to inadequate or absent replies (Most et al., 2010; Tye-Murray, 102 2003). This pattern has also been documented in the longitudinal language development study after cochlear 103 implantation, where pragmatic and social communication outcomes lagged behind structural language gains in many 104 CI users (Tobey et al., 2013), potentially contributing to social exclusion and peer difficulties. Similar difficulties have 105 also been found in narrative skills, in terms of coherence, and in taking into account the eventual lack of common
106 ground (Boons et al., 2013; Crosson & Geers, 2001; Toe & Paatsch, 2018). Nevertheless, on some aspects results are
107 mixed. For example, Socher et al. (2019) found no significant group-level difference in pragmatic language scores
108 between CI and TH children, but observed that 36% of the CI group scored below age norms (standard score <85),
109 compared to just 6% of the TH group — highlighting important within-group variability that may be overlooked by
110 mean comparisons.

111 Recent work has also shown that teenage CI users may exhibit slower speaking rates in repetition, which can affect
112 turn-taking precision and conversational dynamics (Shin et al., 2022). In addition, scholars have begun to investigate
113 other expressive channels that contribute multimodally to the emergence of meaning and the unfolding of dialogue,
114 such as facial expressions, gestures, and prosody (Ambrose, 2016; Le Maner-Idrissi et al., 2020; Panzeri et al., 2021;
115 Socher et al., 2019). A comprehensive assessment of linguistic and pragmatic abilities in Italian children with cochlear
116 implants confirmed difficulties in the paralinguistic scale (evaluating the comprehension and production of several
117 non-speech cues) and the contextual scale (evaluating the child's ability to use appropriate communicative behaviours
118 with respect to different social contexts) (Parola et al., 2024). These difficulties, can lead to misinterpretations,
119 isolation and fewer peer interactions, hindering social competence development (Bat-Chava & Deignan, 2001;
120 Haukedal et al., 2022; Hintermair, 2011; Most, 2007; Vissers & Hermans, 2018).

121 Some scholars attribute DHH children's pragmatic struggle to increased cognitive load in processing auditory
122 information (Henry et al., 2012; Marsella et al., 2017; Pisoni, 2000; Rönnberg et al., 2010), while other studies suggest
123 that these difficulties may simply be related to general language development (Rinaldi et al., 2013). Finally, others
124 scholars suggest that these lasting delays may be due to reduced early social interactions and limited exposure to rich
125 language environments (Matthews & Kelly, 2022; Most et al., 2010; Paul et al., 2020).

126 To sum up, the literature reviewed highlights how the difficulties faced by DHH children, go beyond speech
127 processing vocabulary and syntax, encompassing atypical turn-taking patterns, conversational coherence, managing
128 misunderstandings, pragmatic inferences, and emotion recognition via prosody or facial expression.

129 **1.2 From Acoustic Convergence to Language Processing and Pragmatics**

130 Interlocutors tend to align (converge or adapt)<fnref n="2" /> at multiple levels while interacting with each other. Alignment can be
131 observed for example at the level of acoustic speech features, voice quality, lexical choices, but also non-speech
132 vocalisation (e.g. laughter) (see for example Brennan & Clark, 1996; Giles et al., 2023; Mazzocconi et al., 2025;
133 Pardo, 2006; Pickering & Garrod, 2021; Rasenberg et al., 2020). Greater alignment typically relates to smoother

<footnote n="2">² For a discussion about the use of different terminologies in various fields, see Rasenberg et al., (2020), Rauchbauer & Grosbras, (2020) and Farmer et al., (2018).</footnote>
134 interaction, increased rapport, and positive social outcomes (Lakin et al., 2003; van Baaren et al., 2009). Although the
135 precise mechanisms remain debated, ranging from automatic tight perception-production coupling (Pickering &
136 Garrod, 2004; 2013) to higher order mentalising processes strongly relying on common ground (Clark & Murphy,
137 1982), most authors agree that alignment serve as a low-level mechanism that scaffold higher-order pragmatic
138 coordination — such as turn-taking and relevance — being positively correlated with success in tasks requiring
139 mutual coordination (Fusaroli et al., 2012; Reitter & Moore, 2014). For example, acoustic alignment (e.g. converging
140 on pitch or syllabic rate) signals attunement and may support predictive processing, enabling participants to anticipate
141 turn boundaries or speaker intent — a foundation for pragmatic coordination (Garrod & Pickering, 2009; Pickering &
142 Garrod, 2004). Moreover, alignment in terms of non-verbal vocalisations (e.g. laughter), communicating emotional
143 and cognitive appraisals, is also an effective means to monitor common ground, mutual understanding and respective
144 stances, essential components of dialogue unfolding allowing an effective conversational flow (Mazzocconi et al.,
145 2025). Previous research has indeed shown that the use of laughter and laughter alignment provide valuable insights
146 into cognitive and pragmatic development, as well as socio-cultural attunement (Mazzocconi & Ginzburg, 2022, 2023;
147 Mazzocconi & Priego-Valverde, 2024). Moreover, populations characteristically facing challenges on the pragmatic
148 aspects of communication (e.g. individuals on the Autism Spectrum or with schizophrenic traits) display atypical
149 laughter production, perception and alignment (Helt et al., 2020; Jones, 2009; Lavelle & McCabe, 2012; Polimeni &
150 Reiss, 2006; Reddy et al., 2002; Samson, 2013).

151 More generally alignment at any level can be interpreted as a sign of social alignment, enhancing the cooperative
152 grounding needed for coordinated action (Fusaroli et al., 2012). Alignment streamlines processing by minimizing
153 differences in form and expectation, thereby freeing cognitive resources for managing pragmatic tasks like relevance
154 and coherence (Clark, 1996). Pragmatic repair (e.g., rephrasing or clarifying) often relies on detecting mismatches in
155 alignment. Successful pragmatic coordination frequently involves re-establishing alignment after disruption (Clark,
156 1996).

157 The Interactive Alignment Hypothesis (Pickering & Garrod, 2006, 2013) proposes that lower-level alignment (e.g.
158 acoustic features) functionally supports the achievement of higher-order conceptual alignment. According to this
159 account, such low-level alignment is not only a prerequisite for, but also informative about, the emergence of shared
160 understanding and shared cognitive representations (Gandolfi et al., 2022).

161 Previous work from a developmental perspective has offered insight into the role and interaction of different factors
162 and cognitive underpinnings at play in alignment at different levels: speech rate production, prosody, syntactic, lexical
163 and conceptual alignment, e.g., (Dale & Spivey, 2006; Fernandez & Grimm, 2014; Fusaroli et al., 2023; Jiang et al., 2022; Kruyt et al., 2023; Misiek & Fourtassi, 2022; Wynn et al., 2019; Yurovsky et al., 2016).

165 Despite the relevance of investigating alignment to understand and assess pragmatic processes and conversational dynamics, work on conversational alignment in DHH children (at any level) is scarce. One exception is the experimental work conducted by Freeman and Pisoni (2017), showing that DHH children and adults show slower speech rates and reduced rate matching in a sentence repetition task. Nevertheless, overall conversational convergence across multiple levels in more ecologically valid interactions remains largely overlooked, despite its theoretical and clinical relevance for characterizing and understanding the pragmatic challenges DHH children face in conversation.

## 2. Current Study

171 In the current study we aim at addressing some of the gaps highlighted in the literature reviewed above, conducting a multi-level analysis of conversation in DHH children and TH children in interaction with an adult across different conversational semi-structured and loosely task-oriented contexts. We aim at integrating multiple methods and level of analysis to offer a comprehensive characterisation of conversational dynamics and specific challenges faced by DHH children in social interactions: from “low-level” speech features, laughter and their convergence, to turn-taking dynamics, lexicon, parts of speech and contingent dialogue act use.

178 We embrace the view proposed also in Ostrand & Chodroff, (2021) of alignment as a multifaceted behaviour rather than a unitary concept. Our interest in patterns of convergence across different levels is multifold in motivation: converging patterns can to some extent reflect the interlocutors’ ability to infer the partner’s needs and cognitive state, crucial for effective social interactions, while adjusting speech properties can improve intelligibility and help reduce miscommunication, especially in challenging environments.

183 Notably, in our analysis we pay equal attention both to the child and the adult behaviour, which is often underreported in studies looking at the pragmatic abilities of DHH children, given the significant effect that the (adult) interlocutor can have on child behaviour via the dynamical nature of conversation. Furthermore, investigating convergence in the adult partner is equally interesting since it can facilitate language processing, comprehension and learning, while building rapport.

188 Our study aims at addressing three guiding research questions:

189 (1) At what level of conversational dynamics do DHH and TH children differ during a collaborative semi-structured conversation?
191 (2) How do speakers from the two groups align acoustically and temporally to their interlocutors, and are such (mis-)

192 alignment patterns mirrored at pragmatic levels?

193 (3) To what extent do adults adjust their behaviour when interacting with DHH children, and how might such

194 adaptations influence conversational dynamics?

195 Based on prior literature in DHH children speech rate alignment (Freeman and Pisoni, 2017), pragmatics (e.g. Church

196 et al., 2017; Matthews & Kelly, 2022; Parola et al., 2024; Paul et al., 2020; Tobey et al., 2013) and the Interactive

197 Alignment Hypothesis (Pickering & Garrod, 2006, 2013), we expected that DHH children would show significantly

198 less acoustic features alignment compared to TH children. Moreover, we expected that such lower alignment would go

199 along with a poorer performance on the task as well as a lower conversation quality, pragmatic contingency and turn

200 taking balance. Since previous work has linked laughter use and laughter mimicry to pragmatic skills and development

201 (Mazzocconi & Ginzburg, 2022, 2023; Reddy et al., 2002; Wehrle, 2023), we expected to observe lower occurrences

202 of laughter, speech-laughter and laughter mimicry in DHH children. These expectations informed the selection of our

203 measures and guided the design of our multilevel analytical framework.

204

## 205 **3 Method**

### 206 **3.1 Corpus**

207 Our corpus is constituted by 22 audio-recorded dyadic interactions of around 30 minutes (M = 31.51 ± 2.16)

208 involving nine DHH children and thirteen TH children engaging with an adult (female)

209 during a referential (treasure-hunting) task, periodically alternated with role-reversal sub-tasks (e.g., child-led

210 referential-tasks, child-storytelling).

### 211 **3.2 Participants**

212 Nine French-speaking children aged 5 to 9 years (3 girls, M = 6.3 years, sd = 1.2 years) with moderately severe (56-70

213 dB), severe (71-90 dB) and profound hearing loss (>90 dB<fnref n="3" />) were recruited via the Centre d'Action Médico-Sociale

214 Précoce (CAMSP) and via the Institut Provençal de Suivi des Implantés Cochléaires (IPSIC) at the Salvator Hospital

215 in Marseille. These children have a variety of devices, including bilateral conventional hearing aids (4), one (1) or two

216 (3) cochlear implants, and in one case (1), a bimodal configuration (a cochlear implant in one ear and a hearing aid in

217 the contralateral ear). They received hearing aids at different ages (M = 2.6 ± 2.1 years; range 0;5 years – 6;7 years).

<footnote n="3">³ Thresholds according to the American Speech-Language-Hearing Association (ASHA) classification.</footnote>
218 Details of all children age, sex, type of implantation, months of use, age of implantation and loss with hearing aid is
219 reported in Table 1A in Appendix. All children used their personal hearing devices during the session. At the
220 beginning of each recording, listening checks were performed to confirm that the devices were operating properly and
221 that batteries were sufficiently charged. All of them had no additional disorders, were born from typical-hearing
222 parents, communicate orally, and had language abilities in the norm for their age. Although no formal speech
223 recognition scores were collected to conduct statistical analyses for the current study, all children had previously
224 undergone speech and language evaluations, such as the Batterie d'Évaluation du Langage Oral pour enfants (ELO)
225 (Khomsi, 2001), administered by certified speech-language therapist at their follow-up centres (CAMSP or IPSIC).
226 These evaluations confirmed their functional use of spoken French, with adequate performance in vocabulary,
227 morphosyntax, and sentence-level comprehension and production for their chronological age. The control group was
228 constituted of thirteen French-speaking typical-hearing children aged 5 to 9 (7 girls, M = 7.25 ± 1.3 years) with
229 heterogeneous socio-demographic profiles equivalent to that of the experimental group. They had no known language,
230 cognitive, neuro-developmental or sensory atypicalities or deficits. According to school records and parent report,
231 these children had no history of hearing, cognitive, language, or neurodevelopmental difficulties. The adult was a
232 female fifth-year student in speech and language therapy. She was instructed to interact in a naturalistic and minimally
233 directive manner to ensure consistency across dyads.
234

<figure><img src="image_2.png" /></figure>

## 3.3 Tasks and Procedure

235 The children sit opposite the adult experimenter, in a quiet room. Audio from both participants is recorded with
236 a unidirectional headset (lapel) microphone connected to a ZOOM H4n digital recorder.

<figure><img src="image_3.png" /></figure>

### 3.3.1 Main Map-task

238 A map is placed in the centre of the table so that the child and the adult can see it. On the map multiple items are
239 drawn. These items have been selected according to their frequency of use in French according to the children
240 age (New et al., 2001). The items included in the task were balanced between frequent items (known by the
241 child), infrequent items (likely unknown to the child) and invented items (unknown to the child). The choice
242 of challenging children with unfamiliar terms, was motivated by the aim of investigating the different strategies
243 used to compensate for their lack of knowledge, as well as any conversational failures. The drawings on the map
244 belong to nine semantic categories of items (e.g. bird, ship etc.), multiple exemplars of the same item are present,
245 but differ in terms of physical (e.g. size and colour) or spatial (e.g. at the top, at the corner of the map) features.
246 Participants are engaged in a treasure-hunt map task (MT) structured in 5 sections (MT1-5). The goal for the child is
247 to collect enough hints to discover where the treasure is. These hints are gained by posing questions to the adult
248 experimenter to disambiguate the target item of the category mentioned by the adult. An example instruction from the
249 adult might be "The next hint is hidden behind the bird". As several items may correspond to this description, the
250 child is expected to recognise the ambiguity and implement strategies to find the correct target item among the
251 possible candidates within the category.

252 The instructions provided by the adult to the children are the following: "We are going to play a game which will
253 allow us to find a treasure! To get to this treasure we need to find all the hints hidden behind target items and play
254 games proposed along the way. I can give you some hints, but you can ask questions when my hints are not enough!".

255 The choice of using a referential treasure-hunting task is also motivated by the fact that it makes more salient and
256 crucial the need to resolve breakdown and request clarifications, more so than in a spontaneous conversation elicited
257 to speak about holidays for example. Referential tasks are indeed commonly used for assessing core pragmatic skills
258 and interpersonal coordination because they closely mirror how language is used effectively in real-world situations:
259 choosing words which are clear and informative (appropriate referring expressions), adapt to what the listener (does
260 not) know, monitor the listener's understanding and adjust accordingly, manage ambiguity, clarifying
261 misunderstandings, interactants need to take the others' perspective into account, involve back and forth between
262 interactants allowing to evaluate turn-taking, repair strategies, responsiveness to feedback and adapting language to
263 the listener.

264 **3.3.2 Sub-tasks**

265 The main task is periodically alternated by tasks where the child can be engaged in different types of interactions.

266 These four sub-tasks (ST1-4) have been included in order to help sustain attention, and especially to acquire data from
267 different types of conversation where the roles are more balanced or even reversed as compared to the main task
268 where the adult detains more information than the child and therefore holds a "leading role", and where different
269 levels of cognitive load, working memory, executive functions, and linguistic skills are involved. The sub-tasks are:
270 (1) "Guess who?": the child and the adult have the same set of cards which are not shown to the partner. The
271 child secretly chooses a card and the adult, asking questions, must guess which of the available cards has been
272 chosen by the child -- in this task the roles are reversed as the child detains more information than the adult; (2)
273 "Picture story": the child is given a series of three sequential pictures arranged randomly which s/he has to put
274 back into chronological order to tell the story; (3) "Child Story telling" the adult elicits an unstructured narration
275 asking the child about their holiday or about the plot of their favourite movie; (4) "Find the differences" is a game
276 in which the child has to find the seven differences between two images, by communicating them verbally to the
277 adult. The task is rather difficult for children who are spontaneously led to focus attention and ask the adult for
278 help.

279 In particular, the picture story and the child story telling sub-tasks (somewhat similar to expository discourse), while
280 leaving to the child the main speaker role, are still conversational since interlocutors are engaged in the process of
281 negotiating shared meaning, mutual understanding and the interactional outcome. The story-teller partner must signal
282 understanding and seek clarification to assure the interlocutor that s/he is following the discourse. Story telling
283 requires therefore additional and different demands compared to a referential task, in some respects more complex for
284 young language users. They require precise use of language in terms of semantics and syntax, but also the need to plan
285 the discourse maintaining conceptual and temporal coherence, considering the interlocutor's knowledge and common
286 ground potentially resulting in higher cognitive load and demands in terms of linguistic complexity compared to the
287 main task: carefully consider the perspective of the listener, check for understanding, provide clarification, read
288 nonverbal messages that indicate understanding (Nippold et al., 2005; Westerveld & Moran, 2011).

## 3.4 Turns Annotation

290 All dialogues were manually transcribed using the software Praat (Boersma & Weenink, 2021). Turn segmentation
291 was manually conducted based on the concept of Turn-Constructional Units (Sacks et al., 1974), defined as any
292 segment of spoken language that could potentially complete a speaker's contribution and signal a possible transition to
293 the next speaker. Turn-Constructional Units vary in size and complexity, ranging from single words (e.g., "yes", "no")
294 to full sentences with multiple clauses. Our annotation framework allows for the sequential occurrence of multiple
295 turns by the same speaker, such as when the interlocutor does not take the floor. Additionally, we accounted for
296 overlapping turns, treating backchannels (e.g., listener responses like "uh-huh" or "yeah") produced during another
297 speaker's turn as separate turns. These (fully) overlapping cases will be the focus of specific analyses in our study.

## 3.5 Speech Features and Convergence

299 Acoustic features were extracted using Parselmouth (Jadoul et al., 2018), a Python interface to Praat (Boersma & Weenink, 2021). We describe below how each feature has been extracted and calculated.

301 The fundamental frequency (F0) was extracted using Praat's *To Pitch* function with a frame space of 0.001 seconds
302 and a pitch range of 50 Hz to 700 Hz, adjusted using quantile-based estimates for individual recordings to account for
303 speaker variability. Intensity (amplitude) was computed using the *To Intensity* method with a window length
304 dynamically set based on the estimated minimum pitch.
305 Silences in speech production were automatically detected using the software Praat, selecting individualized 306 parameters and thresholds for each speaker. The total number of syllables within each turn was counted, and the 307 syllabic rate was computed by dividing the number of syllables by the duration of the turns minus the duration of the 308 automatically detected silences. We computed the mean syllable rate and excluded all values which were above or 309 below the two standard deviations per individual (3.7 % of the total).

310 For each variable of interest, we then calculated the mean value per turn. We run statistical analysis applying Linear 311 Mixed Effect models using the *lme4* (Bates et al., 2015) package in R. Each dependent variable was modelled as a 312 function of GROUP (DHH/TH) and ROLE (Child/Adult). Interactions among fixed factors were included as well, 313 while the specific DYAD and TURN were included as random intercepts.

314 To analyse *convergence* on a specific feature between speakers (Adult and Child), we firstly excluded all the turns 315 occurring in full overlap with a turn from the interlocutor, i.e. we removed every turn whose start time and end time 316 were embedded in a longer turn from the interlocutor, in order to analyse only consecutive adjacent turns. The mean 317 value of the acoustic variable of interest (e.g. F0 mean, F0 standard deviation, Syllabic Rate, Mean Intensity (dB) etc.) 318 of turn (X) and the average value of the previous turn (X-1) from the interlocutor were extracted.

319 To evaluate whether convergence on each feature of interest occurred between interlocutors, we followed the 320 procedure used in (Schweitzer & Lewandowski, 2013) to measure static local synchrony (Wynn & Borrie, 2022). We 321 constructed and compared two nested linear mixed-effects models applying the *lmer* function from the *lme4* package 322 (Bates et al., 2015) for goodness of fit. Both models aim at predicting the value of a specific variable characterizing a 323 given turn of one speaker. However, the first model included Role, Group and their interaction with the feature of 324 interest from the partner's preceding turn as a fixed effect; while the second model excluded this interaction. Model 325 comparison was conducted using the *anova()* function, to test whether the inclusion of information from the previous 326 partner's turn would improve the performance of the model. By comparing two nested linear mixed-effects models, 327 we assess whether including the partner's previous feature as a predictor improves model performance. If the model 328 with this interaction fits significantly better, it suggests that the interlocutors' behaviours are linked—indicating 329 convergence. The final formulas used to construct the full and the null LMEMs was thus as follows:

330 full: target utterance ~ preceding utterance * Role * Group + (1 | individual) + (1 | dyad)

331 null: target utterance ~ Role * Group + (1 | individual) + (1 | dyad)
332

## 3.6 Dialogue Acts Annotation

333 Our Dialogue Act annotation is especially focused on the analysis of adjacent pairs of dialogue acts (Schegloff & Sacks, 1973). Our classification is based on the DAMSL (Dialogue Act Markup in Several Layers) model proposed by (Core & Allen, 1997) and on the INCA-A (Inventory of Communicative Acts-Abridged) proposed by Ninio et al., (1994), combined with the classification applied in Tait (1993). We distinguish between Initiating and Responding dialogue acts specific for the Child and for the Adult. Initiating dialogue acts are those aimed to elicit an action from the interlocutor, which correspond to Forward Communicative Functions in the DAMSL model and to "first pair parts" in (Schegloff & Sacks, 1973). On the other hand, Responding Dialogue Acts are those elicited by a solicitation by the interlocutor (Initiating Dialogue Acts), which correspond to Backward Communicative Functions in the DAMSL model and to "second pair parts" by Schegloff & Sacks (1973). The full list of labels used for our annotations are provided in Appendix (Section 4A) with examples. Additionally, we developed a qualitative classification system to evaluate the strategies used by children in resolving the referential conversational task (categorized as Good, Medium, or Poor). The optimal strategy is for the child to question the adult using discriminative questions, progressively eliminating incorrect items, taking into account common ground and previously gained information, to determine the target item and gaining the next hint. Poor strategy is reflected in Random guessing when the available information is too limited for a reasonable guess. This classification was applied to both declaratives and questions produced by the children during the Main task.

349 The full corpus has been annotated for dialogue acts by a speech and language therapist, and inter-annotator agreement calculated on 10% of the sample (10% from the TH dyads and 10% from DHH dyads) between two annotators (927 dialogue acts). For large classes of dialogue acts (declaratives, questions, clarifications, directives, elicitations) we obtain a Krippendorff's alpha of 0.85. For specific subclasses (see Appendix 4A) we obtain a Krippendorff's alpha of 0.84.

354

## 3.7 Laughter Annotation and Mimicry Calculation

355 Laughter annotations have been carried out manually using the software ELAN (Brugman & Russel, 2004). The coding was carried out by one annotator listening to each audio-file until a laugh occurred. The coder then marked the onset and offset of the laugh, distinguishing between laughter not overlapping or overlapping with speech (Laughter/Speech-laughter). Our criteria for laughter identification and annotation are in line with previous work (e.g.,
359 El Haddad et al. (2019); Mazzocconi & Ginzburg (2022)<fnref n="4" />, though adapted since we relied exclusively on the auditory modality. Inter-annotator agreement on laughter annotations was assessed having a second coder for 20% of the 360 conversations (covering 30% of the laughs annotated by the first annotator). For segmentation (onset, offset) we 361 observed an average degree of organisation of 0.74 (Staccato algorithm, Lücking et al., 2012)<fnref n="5" />. The observed labelling 362 agreement on matched annotations was 98% and Cohen's kappa was 0.9. 363

364 Our study focuses on: the occurrence of laughter (frequency), duration, position in relation to speech (laughter/speech- laughter), and to the partner's laughter (Non-/Mimicking). For the purposes of this paper, a Mimicking laugh 365 (produced by interlocutor B) refers to any laugh that shortly follows the onset of a Non-Mimicking laugh (produced 366 by interlocutor A). The following describes our method for identifying Mimicking and Non-Mimicking laughs, where 367 Aᵢ and Bⱼ are the iᵗʰ and jᵗʰ laughs produced by interlocutors A and B, respectively, Tₐₙₐ₆ and Tₐ₆ₐ₅ are the start and 368 stop times, respectively, and ΔT is set to 1 second. In order for laugh Bⱼ to mimic laugh A, Bⱼ must occur after the 369 start time of Aᵢ (1) with an onset before the stop time of Aᵢ with a margin ΔT (1 sec). To avoid duplication, Bᵢ must 370 stop before the start time of laugh Aᵢ₊₁ (2). 371

372 (1) Tₐₙₐ₆ (Aᵢ) < Tₐ₆ₐ₅ (Bⱼ)

373 (2) Tₐₙₐ₆ (Bⱼ) < min{Tₐ₆ₐ₅ (Aᵢ) + ΔT, Tₐ₆ₐ₅ (Aᵢ₊₁)}

374

375 **3.8 Statistical Analysis**

376 All the statistical analyses reported in the following sections were conducted using R (R Core Team, 2024), version 377 4.4.0. The packages *lme4* (Bates et al., 2015) and *emmeans* (Lenth et al., 2022) were used for mixed models, while 378 *ggplot2* (Wickham et al., 2016) was used for graphical exploration.

379 Scripts and raw data will be shared with the final version of the current paper on https://osf.io/.

380 **4 Results**

381 In the following sections, we use the term *Group* to refer to the composition of the dyad (i.e., TH Adult with a DHH 382 Child vs. TH Adult with a TH Child). The term *Role* refers to the two interlocutors within each dyad: the Adult and 383 the Child. For example, when we state that we do not observe differences in adult behaviour across Groups, we mean 384 that the TH Adult behaves similarly whether interacting with a DHH Child or a TH Child. Viceversa, when we state

<footnote n="4">⁴ The annotation protocol followed from Mazzocconi et al. 2022 can be found at https://osf.io/mbv8z.</footnote>

<footnote n="5">⁵ This is a measure based on Thomann (2001, p. 243). It ranges in the interval (-1, 1). A value of 0 corresponds to the agreement expected from random annotations.</footnote>
385 that we do not observe differences in child behaviour across Groups, we mean that DHH children behaves similarly to
386 TH children when interacting with a TH Adult. Finally, the term *Interlocutor* will occasionally be used to indicate the
387 respective partner in the dyad (i.e., the Interlocutor for a Child is always the Adult, and the Interlocutor for the Adult is
388 always the Child).

389

390

**4.1 Completed Tasks/Performance**

391 In our protocol, children participated in a referential conversational task where they had to gather sufficient hints to
392 locate a hidden treasure. This main task (MT) was periodically alternated by sub-tasks (ST) in which the roles of the
393 adult and child were reversed. The total time allocated for gathering hints, completing the sub-tasks, and finding the
394 treasure was approximately 30 minutes. Notably, all TH child – TH adult dyads (N = 13) completed the tasks within
395 the allotted time (mean time ~ 31 minutes, SD = 96 seconds). In contrast, only 5 out of 9 DHH child – TH adult dyads
396 completed all tasks (mean time ~31 minutes, SD = 178 seconds). Specifically, 4 DHH child – TH adult dyads were
397 unable to finish the last two sub-tasks (ST4 & MT 5), which accounted for 13% (mean 4 min, sd 51 sec) of the total
398 time taken by the dyads who successfully completed all sub-tasks and found the treasure (Figure 1). DHH child – TH
399 adult dyads result therefore significantly less likely to complete all the subtasks in the allocated time (Fisher's Exact
400 Test *p* = .02).

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411 The following analyses are aimed at better understanding this dramatic difference in terms of “global” performance in
412 a cognitive and pragmatic complex task. With the aim of investigating at which level of the conversational dynamics
413 differences between the DHH and TH group would emerge, potentially explaining such dramatic difference in
414 behavioural performance, we organised the remaining of the current section from “lower-level” features (e.g., acoustic

415 features) and their interactive alignment to “higher-level” conversational elements (e.g., types of dialogue acts).

## 4.2 Acoustic Features

### 4.2.1 Syllable Rate

418 Children have generally slower syllable rates (Children overall mean = 4.08 syll/sec, sd 0.40) than Adults (Adult

419 overall mean = 5.60 syll/sec, sd 0.98; $\beta$ = -1.75, SE = 0.31, df = 19.98, t = -5.61, p < .000). No differences are

420 observed between TH and DHH conversation ($\beta$ = 0.1, SE = 0.31, df = 39.10, t = -0.43, p = .67) neither in the Role

421 (Adult/Child) by Group Interaction ($\beta$ = 0.39, SE = 0.40, df = 19.91, t = 0.97, p = .34; DHH Child = mean syll/sec

422 3.92, sd 0.34; TH Child = mean syll/sec 4.19, sd = 0.45; Adult in interaction with DHH Child = mean syll/sec 5.68, sd

423 1.31, Adult in interaction with TH Child = mean syll/sec 5.54, sd 0.66) (see Figure S1A). We observe overall a

424 significant effect of the previous turn from the interlocutor in the syllabic rate of the targeted one ($\beta$ = 0.05, SE = 0.02,

425 df = 8789.24, t = 3.01, p = .003) and the model including the syllable rate of the previous turn performs significantly

426 better than the one not including it ($\chi^2_4$ = 19.93, p < .000). This effect is similar across Groups ($\beta$ = -0.02, SE = 0.02,

427 df = 8788.62, t = -0.77, p = .44). We observe a significant effect of Role ($\beta$ = -0.05, SE = 0.02, df = 8787.67, t = -2.54,

428 p = .01) while the three-way interaction Previous turn by Group and Role interaction is not significant ($\beta$ = 0.03, SE =

429 0.02, df = 8787.06, t = 1.11, p = .26, see Figure 2.a). This shows that regardless of the Group, the Adult tends to align

430 more than Children to the Syllable Rate of the previous interlocutor's turn.

### 4.2.2 Fundamental Frequency (F0)

432 As expected, Children show generally higher F0 means (Child mean = 269 Hz, sd 10.1), than the Adult (Adult mean =

433 222 Hz, sd 4.42; $\beta$ = 56.29, SE = 6.74, df = 20.05, t = 8.35, p < .000). DHH conversations are characterized by higher

434 F0 means than TH conversation (DHH dyads mean 259 Hz, sd 7.95; TH dyads mean 236 Hz, sd 6.62; $\beta$ = -14.58, SE

435 = 6.94, df = 38.21, t = -2.10, p < .05) and this effect tend to be larger for Children (Role by Group Interaction, $\beta$ = -

436 15.76, SE = 8.77, df = 20.05, t = -1.80, p = .08; DHH Child = mean F0 287, sd 8.84; TH Child = mean F0 257, sd

437 8.99; adult with DHH Child = mean F0 231, sd 5.11; adult with TH Child = mean F0 216, sd 3.14) (see Figure S1B).

438 We also observe wider F0 variability range in DHH dyads than in TH dyads overall (DHH dyads mean 58.4 Hz, sd

439 10.7; TH dyads 46.7 Hz, sd 4.40; $\beta$ = 11.71, SE = 3.21, df = 38.2, t = -3.64, p < .001), while there is no effect of Role ($\beta$

440 = -4.38, SE = 3.25, df = 19.75, t = -1.35, p = .19) and the interaction between Group and Role is not significant ($\beta$ =

441 0.13, SE = 4.23, df = 19.75, t = 0.03, p = .97) (Adult with DHH Child mean 60.6 Hz, sd 5.44; DHH Child 56.1 Hz, sd

442 11.7; Adult with TH Child 48.8 Hz, sd 1.44; TH Child 44.5 Hz, sd 4.75).
443 Finally, considering the F0 mean of the previous turn from the interlocutor significantly improve the model fit to the data ($\chi^2_4 = 39.4, p < .001$). We observe overall a significant main effect of the F0 of the previous turn ($\beta = 0.07, SE = 0.02, df = 9776, t = 3.99, p < .001$), but not interactions with Group or Role (neither in the two-way interactions and three-way interaction, $\beta = -0.01, SE = 0.03, df = 9776, t = -0.42, p = .68$, see Figure 2.b). This suggests that overall there are no significant differences in how the adult and children align in terms of F0 regardless of the dyad composition.

### 4.2.3 Intensity

450 Turns from TH conversations show significantly higher intensity than turns from DHH conversations (DHH dyads mean = 43.6 Db, sd 8.08; TH dyads mean = 53.0 Db, sd 0.94; $\beta = 10.82, SE = 2.80, df = 30.97, t = 3.86, p < .001$) and 451 Children show significantly higher intensity than the adult regardless of Group (Adult overall mean = 44.3 Db, sd 7.30; Child overall mean = 54.0 Db, sd 1.09; $\beta = 11.36, SE = 2.07, df = 20.08, t = 5.49, p < .001$). The Group by Role 452 interaction is not significant ($\beta = -2.79, SE = 2.69, df = 20.08, t = -1.03, p = .31$, see Figure S1C).

453 Finally, we found a significant effect of the interlocutor's prior turn mean intensity on the intensity of the speaker's 454 current turn ($\beta = 0.11, SE = 0.03, df = 8619.80, t = 4.36, p < .001$). A model excluding the previous turn from the 455 interlocutor performs indeed significantly worse than a model including it ($\chi^2_4 33.2, p < .001$).

456 This effect is slightly more marked in the DHH group ($\beta = 0.09, SE = 0.03, df = 8811.05, t = -2.92, p < .005$) and in 457 the adult ($\beta = 0.07, SE = 0.03, df = 8636.32, t = -2.50, p = .01$). This suggests that overall the Adult tends to align more 458 than children to the intensity of the previous turn. We observe a significant interaction by Group and Role ($\beta = 0.08, 459 SE = 0.04, df = 8869.72, t = 2.05, p = .04$, see Figure 2.c). This shows that while the adult tends to align more than the 460 DHH child, the opposite is true for TH dyads, where it is the child to align more than the adult. 461

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### 4.3.1 Balance between Speakers

474 Computing the difference in speaking time within each dyad (% speaking time adult - % speaking time child) gives an index of balance between speakers (Wehrle, 2023). We observe that the adult have significantly higher percentages of speaking time and this unbalance is greater in DHH dyads (39.5% sd 13.1) than in TH dyads (19.3% sd 10.8) (W = 104, *p* < .001, see Figure 3.a).

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### 4.3.2 Turns and Turn Transitions

489 The analysis of the entire corpus (all subtasks and children) yields 11700 turns. The adult produces overall more turns per minute than the child (Main effect of Role: Adult mean = 8.83, sd 1.26, Child mean = 7.97, sd 1.02; W = 350, *p* = .005). However, there is no significant effect of Group, nor a significant interaction between Role and Group.

490
491
492 Concerning duration of turns, we observe a significant interaction between Group and Role (β = 0.97, df = 0.32, SE = 19.34, t = 3.07, *p* = .006): while the adult produces even longer turns when interacting with a DHH rather than with a TH child (Adult with DHH Child mean = 3.38 s, sd 0.91; Adult with TH Child mean = 2.97 s, sd 0.36), DHH children produce even shorter turns than TH children (DHH Child mean = 1.82s, sd 0.42; TH Child mean =2.35 s, sd 0.41), resulting therefore in a greater asymmetry in turn duration between adult and child (Figure 3.b).

493
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496
497 We also analysed the frequency of turns produced *within* the duration of the partner's turn in complete overlap.
498 Overall, the frequency of turns within the partner's turn are higher in children than adults (W = 95, *p* < .0001, Figure 3.c) but there is no effect of Group nor Role by Group interaction (W = 221, *p* = .7). Concerning durations of turns 499 produced in full overlap with the interlocutor we do not observe any statistically significant effect of Group (β = 0.19,

[Insert Figure 3 here]
501 SE = 0.13, SE = 46.94, t = 1.41, p = 0.17), Role (β = -0.15, SE = 0.10, t = 20.21, t = -1.45, p = .2), or Group by Role interaction (β = -0.08, SE = 0.16, df = 18.67, t = -0.48, p = .6).

503 Finally, children turn transitions are significantly longer than adults (Adult overall mean = 0.7 s, sd 0.15; Child overall mean = 0.99, sd 0.21; β = 0.32, SE = 0.06, df = 20.03, t = 5.05, p < .0001, Figure 3.d) regardless of group (Role by Group interaction: β = -0.06, SE = 0.08, df = 19.94, t = -0.7, p = .5) and in absence of a Group main effect (β = 0.12, SE = 0.08, df = 33.23, t = 1.5, p = .14) (Adult with DHH Child mean = 0.63 s, sd 0.78; Adult with TH Child mean = 0.75, sd 0.29; DHH Child mean = 0.95, sd 0.26; TH Child mean = 1 s, sd 0.31).

## 508 4.4 Lexical Diversity and Parts of Speech Distribution

509 In Appendix 3A we report supplemental analyses and discussion concerning the variety of lexicon and parts of speech (i.e. grammar categories) used by the adult, DHH children and TH children when interacting with each other. Notably, we observed marked differences in the adult depending on whether she is interacting with a DHH child or TH child (e.g. less varied lexicon, simpler grammatical structures, higher use of pronouns).

## 513 4.5 Dialogue Acts

### 514 4.5.1 Initiation of Dialogue Acts

515 When examining the percentage over the total Dialogue Acts produced, we observe DHH to utter significantly less questions than TH children (DHH Child mean = 39% of DAs, sd 9.9; TH Child mean = 63% of DAs, sd 17.2; W = 12, p = .001), while producing significantly more clarification requests (DHH Child mean = 16% of DAs, sd 6.8; TH Child mean = 7% of DAs, sd 2.5; W = 107, p < .001) and declarative statements (DHH Child mean = 45% of DAs, sd 12.6; TH Child mean = 29.4% of DAs, sd 17.2; W = 97, p = 0.01) than TH children (Figure 4.a).

520 To interpret the result concerning declarative acts, it is important to consider that they most frequently relate to the choice of a target item (e.g. "it's the red one!"). The amount of declaratives produced to find the target item depends upon the strategy used by children: a trial-and-error strategy (i.e. guessing randomly the target item) would lead to the production of more declaratives and less questions as compared to a strategy where guessing attempts are put forward only when enough cues have been gathered. Figure 4.b shows indeed that DHH children tend to use inefficient strategies to identify the target item during the game, insofar as they attempt to guess randomly more often than TH children (Random guesses over total declaratives: DHH Child mean = 77.3%, sd 10.5; TH Child mean = 52.4%, sd 19.6; W = 102, p = .002) (see Sec. 3.6 for Strategy annotation).

### 528 4.5.2 Response to Adult Dialogue Acts
529 Considering the responsiveness to Dialogue Acts initiated by the adult, DHH children tend to show higher percentages of Failure (Inappropriate or No response) compared to TH children (W =1133, p = .08) (Figure 4.c). Significantly higher percentages of Failure are observed in DHH children specifically in response to a particular type of adult dialogue acts: Directives intended to elicit questions from the children (e.g. "You need to ask me a question when you don't know") ($\chi^2 = 59.94, p < .001$). While TH children do not respond more frequently than DHH children ($\chi^2 = 8.83, p = .002$), DHH children exhibit significantly more Failures than TH children ($\chi^2 = 59.39, p < .001$) in responding this specific dialogue act (see Figure 4A in Appendix).

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## 4.6 Laughter

544 Over the full corpus, 830 laughs were identified and annotated: 669 in the 13 TH dyads (376 produced by children) and 161 in the 9 DHH dyads (89 produced by children). Laughter is overall significantly more frequent in the TH dyads than in the DHH dyads (W = 86, p < .001). Nevertheless, this effect is especially due to a marked difference in the Adult who laughs significantly more when interacting with TH children than DHH children (Adult with DHH Child mean laughter occurrences = 8, sd 2.96; Adult with TH Child mean laughter occurrences = 22.54, sd 6.6; W = 2, p < .001; DHH Child mean laughter occurrences = 9.9, sd 10.7; TH Child mean laughter occurrences = 31.3, sd 33.7; W = 34, p = .11). Laughter duration does not differ across Groups ($\beta$ = -0.07, SE = 0.10, df = 33.73, t = -0.74, p = 0.46), nor between Roles ($\beta$ = -0.11, SE = 0.08, df = 815.97, t = -1.36, p = .17), nor in their interaction ($\beta$ = 0.08, SE = 0.09, df = 817.96, t = 0.90, p = .37). Speech laughter is less frequent in DHH dyads compared to TH dyads ($\chi^2$ = 8.0, df = 1, p < .005). This effect is essentially driven by a strong difference in children (DHH Child mean = 22.47%; TH Child mean = 40.96%; $\chi^2$ = 9.72, df = 1, p = .001), but not in adult (Adult with DHH Child mean = 12.5%; Adult with TH Child mean = 14.68%; $\chi^2$ = 0.08, df = 1, p = .78). Mimicking laughter occurrences are overall rarer in the DHH group than in the TH group (DHH group mean = 6.19, sd 6.7; TH group mean = 14.87, sd 18.2; $\chi^2$ = 7.83, p = .005). This is the case for both adults (Adult with DHH Child mean = 6.58%, sd 8.25; Adult with TH Child mean = 14.9, sd
558 16.11; $\chi^2 = 3.91, p < .05$) and children (DHH Child mean = 7.76%, sd 10.86; TH Child mean =18.46%, sd 17.31; $\chi^2 =$
559 3.94, p < .05). Figure 5.b and 5.c represent respectively Percentages and Transitional Probabilities of Laughter
560 Mimicry across Group and Role.

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571

5. Discussion

572 Our multilevel analysis of semi-structured adult–child conversations highlights specific pragmatic challenges in orally
573 educated children who are DHH, using hearing technology without sign language exposure. Only 55% of DHH child-
574 TH adult dyads completed every sub-task in the allocated time, whereas 100% of TH child-TH adult dyads did so. The
575 worst performance on pragmatically complex conversational tasks in the DHH-TH dyads, goes along with greater
576 speaking time adult-child imbalance, suboptimal strategies to solve the task (preference for declarative random
577 guessing from the child), lack of contingency and adjacency in responding to adult dialogue acts, less laughter,
578 speech-laughter and lower laughter alignment. On the other hand, acoustic convergence in F0, intensity and syllable
579 rate, as well as lexical diversity and turn transitions timings, did not show differences between Groups.

580 Two potentially complementary factors likely contribute to the asymmetry in performance and pragmatic behaviour.
581 First, degraded auditory input elevates cognitive-processing demands, taxing attention and working memory and
582 leaving fewer resources for monitoring turn structure, pragmatic contingencies, focus on complex problem-solving
583 and collaborative activities (Boerrigter et al., 2023; Castellanos et al., 2016; Marschark et al., 2007; Ohlenforst et al.,
584 2017). Second, reduced early access to rich spoken language limits opportunities for incidental learning of
585 conversational repair, role alternation, and other pragmatic rules (Matthews & Kelly, 2022; Most et al., 2010; Paul et
586 al., 2020). Together, these constraints, despite acoustic recovery through cochlear implants or prostheses, can affect
587 the flow of interactions and the effectiveness in accomplishing collaborative tasks requiring sustained attention,
588 language processing and pragmatic coordination (Crowe & Dammeyer, 2021).

589 Notably, we gave equal consideration to both the children and the adult interacting with them, emphasizing their
590 reciprocal influence on interactive behaviour. We observed significant differences in adult coordination, lexicon and
591 responsiveness when interacting with DHH versus TH children— even when DHH children behaved similarly to their
592 TH peers. These findings offer valuable insights for practitioners, families, and educators, supporting the development
593 of tailored strategies to foster conversational and pragmatic skills in DHH children (see Section 5.4).

594 It is also important to emphasize within-group variability. Echoing Socher et al. (2019), our data show that while some
595 DHH children showed interactive patterns similar to TH children, others struggled markedly. Mean differences
596 therefore can mask individual patterns; future work with larger samples should identify predictors, such as age at
597 implantation, auditory thresholds, or parent–child interaction style, that could explain this dispersion.

598 In the following sections, we address our research questions by interpreting the findings in greater detail, situating
599 them within relevant theoretical frameworks and previous literature. Our discussion is structured across different
600 levels of analysis—ranging from acoustic features and convergence to specific interactional dynamics, including turn-
601 taking, laughter responsiveness, and the use, responsiveness, and balance of dialogue acts.

602 Our multilevel approach clarifies how certain dyads involving a TH adult and a DHH child while engaged in the
603 conversation and activity, struggle to assess, negotiate and maintain mutual understanding and alignment across
604 communicative layers, from acoustic alignment to pragmatic contingency.

## 5.1 At which levels of conversational dynamics do DHH and TH children differ during a collaborative semi-structured conversation?

### 5.1.1 Turn Taking Dynamics: Speaking Time Balance

608 In terms of turn-taking and speaker balance, a key finding was the greater conversational asymmetry in DHH dyads.

609 Adults interacting with DHH children spoke for significantly longer durations than when engaging with TH children,
610 while DHH children produced notably shorter turns than TH peers. This imbalance may reflect adult conversational
611 prominence, potentially limiting the child's opportunities for active participation (Cruz et al., 2013; Holt et al., 2012).

612 Alternatively, it may indicate the adult's rapid adaptation to the conversational style of DHH children. Notably, turn
613 transition timings did not differ between groups. If the imbalance were solely due to adult prominence, we would
614 expect shorter turn transitions and more overlaps. Conversely, if it stemmed from DHH children's unresponsiveness,
615 longer child transitions would be expected. The absence of such differences in turn transition timings suggests that
616 turn-taking dynamics are rapidly adjusted based on the interlocutor's conversational style. The speaking time
617 imbalance may partly result from the additional processing challenges faced by DHH children, leading to reduced
618 verbal contributions and, over time, fewer opportunities for language development (Davis et al., 2021).

619 The slower transition times observed in children across groups may reflect the adult's intentional adjustment to allow
620 extra time for children to process cognitively demanding tasks, particularly in the referential treasure-hunting task,
621 which often requires visual search alongside verbal processing. Notably, we found no significant differences between
622 DHH and TH children in the number of turns produced in complete overlap with the adult's speech. These
623 overlapping turns were typically brief and primarily consisted of backchannels and feedback. These play a crucial role
624 in conversational dynamics, enabling the primary speaker to monitor listener engagement and shared understanding
625 (Bavelas & Gerwing, 2011). These results contrast with previous findings reporting fewer backchannels in DHH
626 children interacting with their peers (Paatsch & Toe, 2016), possibly due to different social, affiliative and cognitive
627 demands compared to interaction with TH adults. Our findings contribute to a growing body of research on turn-
628 taking in DHH individuals, which has thus far yielded mixed results. While some studies (e.g., Chitgar et al., 2022;
629 Guerzoni et al., 2016; Hutchins et al., 2017), report patterns comparable to TH peers, others (Most et al., 2010; Rinaldi
630 et al., 2013) show more pronounced differences.

631 On the other hand, the observed asymmetry in speaking time and turn duration in DHH dyads supports the idea that
632 DHH children may adopt a more passive role in conversations, which could in turn reduce their opportunities for
633 active participation and learning. These turn-duration asymmetries are especially important when considered within
634 the multilevel coordination framework described above: while DHH children may exhibit surface-level alignment in
635 acoustic features, their reduced contribution timing and turn balance point to fragilities in higher-order coordination.
636 This highlights the need to consider how difficulties in timing and speaker-role negotiation can coexist with preserved
637 acoustic alignment or lexical behaviours, reinforcing the view that successful communication requires the integration
638 of multiple behavioural dimensions. These results highlight the need for further investigation into the factors
639 influencing turn-taking behaviours in DHH children and how intervention might promote more balanced
640 conversational dynamics.

641 5.1.2 Dialogue Acts: Contingency, Adjacency and Strategy

642 In line with previous studies, we observed that conversational contingency (the extent to which an utterance is
643 appropriately and meaningfully linked to the preceding discourse) and adjacency (the expected sequencing of paired
644 conversational turns such as question-answer or greeting-greeting) stand out as major challenges for DHH children
645 (Church et al., 2017; Crowe & Dammeyer, 2021; Ibertsson et al., 2009; Most et al., 2010; Paatsch & Toe, 2016; Tye-
646 Murray, 2003). These seem to be more subtle skills than turn-taking and acoustic convergence, crucial for facilitating
647 smooth social interaction, building and maintaining relations and friendships (Stinson & Whitmire, 2000).

648 Our dialogue act analysis showed a more frequent use of declarative statements and clarification requests by DHH
649 than by TH children. The high frequency of declaratives (see Figure 3b) reflects their reliance on random guessing
650 over incremental questioning to identify targets, suggesting difficulties in understanding the task and integrating cues
651 during problem-solving (Nicastri et al., 2021). Additionally, DHH children struggle to respond effectively to adult
652 directives intended to elicit questions, persisting in this difficulty throughout the task. This may stem from challenges
653 in understanding the task, metacognitive difficulties in assessing their comprehension, or reluctance to seek
654 clarification on deeper misunderstandings (Borgna et al., 2011; Church et al., 2017; Marschark et al., 2007; Morrison
655 et al., 2013). While DHH children make frequent clarification requests, particularly general ones (Ibertsson et al.,
656 2009; Jeanes et al., 2000; Paatsch & Toe, 2016), the significance of these requests would be clearer with a
657 quantification of conversational breakdowns (Dammeyer, 2012; Lloyd et al., 2005), which our study did not include.

658 The literature on repair sequences is mixed: some report no difference in repair frequency (Church et al., 2017), while
659 others note more clarification requests (Ibertsson et al., 2009; Samuelsson & Lyxell, 2014) or increased breakdowns
660 and silences (Tye-Murray, 2003) in DHH children. Notably, DHH children are more likely to prompt repetition but
661 avoid initiating repairs when misunderstandings stem from omissions by hearing peers, perhaps to avoid appearing
662 disruptive, or due to insufficient monitoring of their own comprehension (Borgna et al., 2011; Morrison et al., 2013).

663 Since avoiding repair can cause major breakdown in conversation, addressing this issue should be a priority in
664 interventions (Church et al., 2017). These findings offer a window into pragmatic coordination at the dialogue act
665 level: while children may produce linguistically well-formed utterances, they often struggle to use those utterances in
666 context-sensitive ways that ensure mutual understanding, coherence and smooth coordination. This dissociation
667 between form and function reinforces the need for a multilevel approach, one that considers not only lexical or
668 acoustic behaviour, but also how these behaviours are used in interactional contexts (pragmatics).

669 We did not observe differences between DHH and TH children in the appropriateness and quality of response to
670 various questions types, contradicting previous findings that DHH individuals struggle with yes/no questions due to
671 intonational cues (Most & Frank, 1991; Most & Peled, 2007; Peng et al., 2007). This discrepancy may reflect
672 advancements in hearing technologies in the last decades (Chatterjee et al., 2024; Park et al., 2025).
673 Concerning the dialogue act pairs initiated by the adult, we observe more questions when interacting with DHH
674 children than when interacting with TH children. This pattern may be motivated by the intention of supporting and
675 scaffolding the interactional flow or elicit more language from the interactional partner which have the tendency of
676 producing shorter turns (e.g. Lloyd et al., 2001) and struggling more with the conversational flow. Notably, in some
677 sub-tasks the adult often interrupted DHH children's narratives, not only for clarification, but also to structure
678 expository discourse and storytelling. Although not the primary focus of this work, DHH children's narratives often
679 showed omitted referents, ambiguous pronouns, or poor coherence, patterns previously documented in the literature
680 (Boons et al., 2013; Lloyd et al., 2005; Most et al., 2010; Paatsch & Toe, 2016). The tendency of adults to dominate in
681 terms of speaking time and structure, is in line with previous research by Toe et al., (2007).

682 5.1.3 Laughter, Dialogue and Pragmatics

683 Laughter was significantly less frequent in DHH dyads, particularly for the adult (Section 4.6). While children's
684 laughter frequency did not significantly differ between groups, the lowest values were predominantly found in DHH
685 children, reinforcing the idea that conversational partners influence each other (Fusaroli et al., 2014).

686 DHH children also produced significantly less speech-laughter than TH children, a behaviour observed long after
687 speech emergence (Mazzocconi & Ginzburg, 2022) despite early laughter onset (Nwokah et al., 1994; Oller et al.,
688 2021), suggesting that speech-laughter may require more complex pragmatic and interactional abilities. Only TH
689 children displayed speech-laughter rates comparable to adult-adult interactions (Devillers & Vidrascu, 2007;
690 Mazzocconi et al., 2020; O'Connell & Kowal, 2005; Trouvain, 2001). The adult's speech-laughter frequency was
691 significantly lower than in adult-adult conversations, likely due to the structured nature of the task and her role as a
692 speech therapist, which may have led to more controlled speech, particularly when interacting with DHH children.

693 Laughter mimicry was also less frequent in DHH dyads, particularly for DHH children as compared to TH children.
694 This could indicate lower conceptual alignment (Gandolfi et al., 2022), as laughter is informative about cognitive
695 appraisals (Ginzburg et al., 2020; Mazzocconi et al., 2020). Alternatively, DHH children's higher cognitive load in
696 speech perception (Marsella et al., 2017) may reduce predictive processing (Pickering & Garrod, 2004, 2013) reducing
697 even non-speech alignment. Concurrently, the structured setting, resembling speech therapy, might have reduced
698 affiliative motivation and therefore alignment, especially for DHH children who have stories of prolonged, often
699 intense, speech and language therapy treatments.

700 DHH children and the adult interacting with them showed markedly lower laughter mimicry (8% and 7%,
701 respectively) compared to typical adult-adult interactions (~35%; e.g., (Mazzocconi et al., 2020; Smoski &
702 B chorowski, 2003; Vettin & Todt, 2004). This may be due to the fact that laughter mimicry reflects shared appraisals
703 and relies on mutual comprehension and common ground, which cannot always be assumed in DHH interactions.
704 From a multilevel coordination perspective, laughter and speech-laughter serve as affective and pragmatic signals that
705 can reveal interlocutors alignment not just acoustically or lexically, but cognitively and conceptually. Its reduced
706 presence highlights deeper difficulties in establishing common ground and emotional resonance in DHH dialogues.
707 Laughter use and production seem thus closely tied to conversation quality and differ significantly between DHH and
708 TH children, and between their respective adult interlocutors. Adult laughter behaviour is influenced by the child's
709 pragmatic and cognitive abilities. However, this, even when intended to support interactions, may unintentionally
710 inhibit positive dynamics that foster learning and engagement, such as shared enjoyment (Pinheiro et al., 2017;
711 Savage et al., 2017). The absence of these dynamics can negatively impact conversation quality (Reece et al., 2023),
712 relationship building (Dunbar, 2022), focus and learning outcomes (Esseily et al., 2016; Savage et al., 2017). These
713 findings contribute to a broader pattern emerging in this study: while some surface behaviours appear preserved,
714 higher cognitive, affective and timing-sensitive cues like laughter reveal how fragile deeper-level pragmatic
715 coordination remains (Parola et al., 2024; Socher et al., 2019).

716 **5.2 How do speakers from the two groups align acoustically and temporally**
717 **to interlocutors? Are such alignment patterns mirrored at pragmatic levels?**

718 Acoustic analyses reveal differences between DHH and TH children. DHH children exhibit higher F0 means and
719 variability, lower amplitude means and variability, and reduced phonation time (Myszel & Szkielkowska, 2020).
720 These features, linked to reduced auditory feedback, subglottal pressure control, vocal tension, or compensatory
721 behaviours for intelligibility, are well-documented (Ashjaei et al., 2024; Das et al., 2013). Greater reliance on visual
722 cues may reduce the need for loudness, contributing to lower speech intensity (Micula et al., 2025). Reduced intensity
723 can though affect conversation quality, as higher and varied loudness helps engage and maintain interlocutors'
724 attention, correlating with conversation enjoyment (Reece et al., 2023).
725 DHH children tend to have lower syllable rates than TH peers. Speech rate however is linked to traits such as
726 competence (Smith et al., 1975), persuasiveness (Miller et al., 1976), and intelligence (Murphy et al., 2003), and is
727 positively correlated with conversation enjoyment (Reece et al., 2023). These aspects should be addressed by
728 practitioners, as modulating intensity, F0, and speech rate impacts conversational quality, engagement, interlocutors'
729 impressions and relationships, which influence quality of life.
Despite differences in speech acoustics, DHH children tend to adapt to the interlocutor's acoustic features, showing convergence in syllable rate, F0, and intensity. While children show less convergence than adults, there are no significant group differences. This contrasts with Freeman & Pisoni (2017) and Shin et al. (2022), who found slower speech-rate and lower convergence in DHH individuals during a sentence repetition task. Our findings suggest that, in interactive tasks -- despite several difficulties in acoustic perception (Holt et al., 2018; Jiam et al., 2017; Torppa et al., 2014) -- DHH children maintain a tendency to align with their interlocutor's speech rate, which is a positive pattern promoting intelligibility, cognitive processing, and interpersonal rapport (Borrie & Liss, 2014; Most et al., 2010).

According to the Interactive Alignment Model (Pickering & Garrod, 2006, 2013), lower-level alignment supports higher-level pragmatic and conceptual alignment, and may be disrupted by cognitive load. Our data supports the interpretation that DHH children preserve a tendency to align at the acoustic level despite increased processing demands. However, this alignment does not guarantee communicative success, as evidenced by their lower task completion rates and pragmatic coordination difficulties. In line with Ostrand & Chodroff (2021), we view alignment not as a unified phenomenon but as a constellation of loosely connected behaviours. In this context, our findings underscore the importance of examining how alignment unfolds across multiple levels of interaction, and how alignment at one level (e.g., F0, syllabic rate) may co-exist with misalignment at others (e.g. dialogue act contingency, laughter use).

## 5.3 Do adults adjust their behaviour when interacting with DHH children?

### How might such adaptations influence conversational dynamics?

Across the various levels of analysis, we consistently observe significant differences in adult behaviour depending on whether they are interacting with a DHH or TH child (Turn Taking Dynamics Sec. 5.1.1, Dialogue Acts Sec. 5.1.2, Laughter 5.1.3, Acoustic Features Sec. 2A and Parts of Speech Sec. 3A.2). These differences are intrinsically linked to the dynamical nature of conversation, where individual behaviours influence the interacting partner, reinforcing the notion that conversation displays dynamical complexity (Shockley et al., 2009). Adults interacting with DHH children exhibited changes not only in dialogue structure but also in speech acoustics modulation, lexical and syntactic choices, and laughter patterns, suggesting systematic adaptation across multiple communicative levels. Nevertheless, it is important to emphasize that while adults often adapt their behaviour to support, sustain, or compensate for challenges faced by the child, these adaptations can, in turn, reinforce the very behaviours that prompted them.

Previous studies have shown that frequent caregiver directives can negatively impact early language development (Hart et al., 1997; Lederberg & Everhart, 2000; Nelson, 1973; Taylor et al., 2009). Similar patterns have been
759 observed in interactions with DHH children using cochlear implants (Cruz et al., 2013; DesJardin & Eisenberg, 2007;
760 Fagan et al., 2014; Holt et al., 2012), with adverse effects on language and vocabulary outcomes (Cruz et al., 2013;
761 Holt et al., 2012). While these directives are often intended to scaffold language use, they may inadvertently limit
762 children's spontaneous responses rather than encourage them. In contrast, caregiver responsiveness, characterized by
763 contingent and temporally aligned utterances, has been identified as a strong predictor of vocabulary growth (Tamis-
764 LeMonda et al., 2014; Warlaumont et al., 2014). Our findings reveal that adult adaptations in interactions with DHH
765 children are not restricted to isolated behaviours but emerge as broader coordination strategies. Longer turns, simpler
766 lexicon and grammatical structure, lower rates of laughter and laughter mimicry, and increased use of direct
767 questioning form a coherent pattern of support that affects both linguistic and affective alignment. Although
768 congenital auditory deficits are the primary cause of language difficulties in DHH children, environmental factors can
769 have a great impact in shaping their language development trajectories, especially in their interactional use. Thus,
770 understanding how adult scaffolding evolves across modalities provides insight into both the adaptive and potentially
771 constraining dynamics of conversation when children face specific pragmatic challenges.

772 **5.4 Theoretical and Practical Implications**

773 These findings have significant theoretical and practical implications for understanding, evaluating, and supporting
774 communication in DHH children. Theoretically, this study contributes to models of language development and social
775 interaction by emphasizing the role of auditory feedback in shaping conversational dynamics, turn-taking, and
776 pragmatic skills (Aubanel et al., 2011; Beechey et al., 2018; Petersen et al., 2022; Pham & Karuza, 2023). The
777 observed differences in acoustic features, dialogue act contingency, and non-speech vocalizations between DHH and
778 TH children highlight the complex interplay between early auditory access and linguistic, cognitive, and social
779 development. These results reinforce the need for ecological approaches to examine how children adapt their
780 communicative behaviours in response to auditory challenges (Keidser et al., 2020; Lunner et al., 2020), as well as
781 how primary sensory deficits can affect broader developmental trajectories and social relationship formation, which
782 are crucial for long-term well-being (Cummings, 2011; Helland et al., 2014). Notably, despite their reduced acoustic
783 resolution in speech perception, DHH children in our semi-spontaneous conversational settings still exhibit acoustic
784 convergence with their interlocutors, in contrast to what had been observed by Freeman & Pisoni (2017) and Shin et
785 al., (2022) in controlled experimental settings concerning speech-rate. However, this ability to align at lower levels
786 coexists with challenges in task completion and maintaining conversational fluidity. These findings call for a
787 reassessment of predictions from the Interactive Alignment Hypothesis proposed by Pickering and Garrod (2006,
788 2013), which suggests that alignment at lower levels is both a prerequisite for and a consequence of optimal alignment
789 at higher conceptual and conversational levels (Gandolfi et al., 2022). Our results indicate that while cochlear implants
790 and other prosthetic devices help compensate for certain low-level perception deficits, they do not necessarily enable
791 alignment at higher pragmatic levels. Our data align with Ostrand & Chodroff (2021), proposing that alignment occurs
792 at different levels within the same dialogue, with low-level alignment persisting even under cognitive load, but not
793 extending to higher levels like emotional vocalizations or dialogue act contingency.

794 Practically, these findings provide valuable insights for educational and therapeutic interventions aimed at enhancing
795 communication in DHH children. They underscore the need for a comprehensive approach that considers not only
796 auditory recovery but also the complex interplay between early auditory challenges and later linguistic, cognitive, and
797 social factors (Morgan et al., 2021). Despite compensation, hearing impairment affects communication, reinforcing
798 the need to understand its impact on conversational dynamics and social interactions. This aligns with prior research,
799 showing that auditory recovery alone does not eliminate language challenges, particularly in pragmatic skills
800 (Matthews & Kelly, 2022; Most et al., 2010; Paul et al., 2020; Peterson & Siegal, 1995; Weisel & Bar-Lev, 1992).

801 While more research is needed to understand the interplay of auditory, developmental, and environmental factors, it is
802 crucial to raise awareness about the challenges DHH children face in social communication, even when auditory
803 recovery and some linguistic skills are well-developed. Pragmatic difficulties, though not the root cause of challenges,
804 are vital for quality of life, as they affect relationship-building (Cummings, 2011; Patel et al., 2021).

805 We advocate for targeted interventions addressing a broad range of pragmatic communication skills (Arcara &
806 Bambini, 2016; Most et al., 2010; Paatsch & Toe, 2016; Parola et al., 2024; Tuohimaa et al., 2023), alongside
807 encouraging interactive adult behaviours that support pragmatic development and generalization across different
808 contexts. Peer interactions should be integrated into interventions, as they are significantly different from interactions
809 with adults and crucial for pragmatic skill development (Blum-Kulka, 2008; Ibertsson et al., 2009; Stivers et al.,
810 2018).

811 While our study did not directly measure metacognitive competences, some of the observed patterns suggest that
812 children may struggle to evaluate their own understanding and information needs. In particular, they often failed to
813 seek clarification when needed and repeatedly relied on suboptimal strategies, such as making random guesses,
814 showing that they had not grasped the task. This was especially apparent in their persistent difficulty responding
815 appropriately to the adult's prompts aimed at eliciting questions, indicating a limited awareness of the referential
816 ambiguity or the task's goals. Taken together with previous findings (Borgna et al., 2011; Morrison et al., 2013;
817 Church et al., 2017), these behaviours may reflect reduced metacognitive monitoring beyond challenges in auditory
818 perception. For instance, Church et al. (2017) found that children with hearing loss were more likely to prompt
819 repetition (related to failure in reliable acoustic perception), yet less likely to initiate clarification when
820 misunderstandings arose from omissions by hearing peers. These observations suggest that fostering self-monitoring
821 and awareness of informational gaps may be beneficial. Interventions promoting such metacognitive awareness, as
822 proposed by Gaile & Adams, (2018), could enhance engagement in both structured and spontaneous conversation.

823 This study also has implications for designing inclusive communication strategies for adults interacting with DHH
824 children. Training programs for teachers, caregivers, and peers should emphasize responsiveness and the creation of
825 supportive and engaging conversational environments that accommodate DHH children’s needs while fostering their
826 ability to generalize these skills across different settings and interactional partners, particularly hearing peers (Hadley
827 & Rice, 1991; Leech et al., 2018).

828 Importantly, fostering enjoyment in interactions is crucial, as it motivates further interaction, enhances learning, and
829 supports relationship development (De Felice et al., 2023; Gruber et al., 2014; Lisman & Grace, 2005; Manninen et
830 al., 2017; Pinheiro et al., 2017; Ripolles et al., 2018; Scott et al., 2022).

831

# 6. Limitations

832 While this study provides valuable insights into the communication dynamics of DHH and TH children, several
833 limitations must be acknowledged. The relatively small sample size limits the generalizability of the findings and
834 reduces statistical power to detect subtler effects. Additionally, the semi-structured nature of the task, while useful for
835 ensuring consistency, might not fully capture the variability and spontaneity of real-world conversational interactions.

836 The study also focuses on dyadic exchanges in a quiet environment, which may not reflect the complexities of group
837 or multi-party (“noisy”) interactions that children frequently encounter in ecological settings. Furthermore, the fact
838 that the adult interlocutor was the same across all dyads and aware of the child group membership, may introduce bias
839 and individual differences in conversational style, tone, or responsiveness could differentially influence the children’s
840 performance depending on hearing status, sex, and age. Moreover, individual differences within the DHH group, such
841 as the degree of hearing loss, use of assistive devices, and language exposure, and their impact on the patterns
842 observed, cannot be reliably tested in such a small sample size.

843 Our taxonomy and analysis of dialogue acts focus primarily on adjacent pairs, defined as fundamental conversational
844 units consisting of two functionally related turns (e.g., a question and an answer, or a greeting and a return greeting,
845 Schegloff & Sacks, 1973). While our coding scheme allows the same dialogue act to function both as a Response to a
846 previous act and as an Initiation for a subsequent one, we did not specifically examine the “third turn” or the dynamics
847 that may emerge across groups at this level. Future studies should focus more specifically on this matter, as previous
848 research indicates that a key conversational difficulty for DHH children may lie in extending and sustaining
849 conversations beyond adjacent pairs (Paatsch & Toe, 2014; Toe & Paatsch, 2018). Finally, the reliance on acoustic
850 and pragmatic measures without incorporating multimodal cues, such as gestures, eye-gaze or facial expressions (not
851 available in the current dataset), may overlook the use of other meaning making signals and compensatory strategies
852 employed by DHH children in face-to-face communication. These limitations highlight the need for more multimodal
853 approaches in future research considering larger samples.

854

# 7. Conclusion

855 This study highlights the complex communication challenges faced by DHH children, including differences in
856 conversational dynamics, pragmatic strategies, and non-speech vocalizations like laughter. While they maintain some
857 interactive convergence (e.g. syllable rate, F0, intensity), they struggle with task completion, conversational balance,
858 and efficient pragmatic strategies. Additionally, reduced laughter, speech-laughter and mimicry suggest cognitive-
859 social barriers to engagement and conceptual alignment. Notably, differences emerge not only in DHH children but
860 also in the adult interacting with them, emphasizing how interlocutors influence each other. Educators and
861 practitioners should be aware that well-intended efforts to scaffold conversation may unintentionally hinder
862 engagement and learning. Intervention should prioritize contingency and adjacency, ensuring skills generalize to peer
863 interactions, which are essential for social development, bonding and life quality (Cummings, 2011; Stinson & Foster,
864 1999; Yont et al., 2002). These findings underscore the importance of integrative approaches that combine auditory,
865 linguistic (including speech and non-speech elements), (meta) cognitive and social aspects to foster effective
866 communication skills and social integration in DHH children.

867

868 Acknowledgments

869 We are heartfully grateful to all children who participated in the recording and to their families. This
870 research was funded by the French National Research Agency under grants ANR-21-CE28-0010 (awarded
871 to to DS, LL & RB) and ANR-17-EURE-0029 (NeuroMarseille). This work, carried out within the Institute
872 of Convergence ILCB, was also supported by grants from France 2030 (ANR-16-CONV-0002), the French
873 government under the Programme «Investissements d'Avenir», and the Excellence Initiative of Aix-
874 Marseille University (A*MIDEX, AMX-19-IET-19 004).
876 **Data Availability Statement**

877 The raw datasets and the scripts employed for the analysis during the current study will be publicly shared in
878 the final version of the manuscript on www.osf.io. The audio files analysed are not publicly available due to
879 ethical and privacy restrictions, but are available from the corresponding author on reasonable request.

880

881 **Ethics Statement:** All children and their parents were informed of the procedure of the study, which was
882 approved by the Sud Méditerranée V Ethics Committee (ID RCB: 2020-A02556- 33). All parents provided
883 informed consent prior to the inclusion of their children in the study. Data were collected and analysed
884 anonymously to protect participants’ privacy and confidentiality.

885

886 **Authors Contributions:** CM contributed to conceptualisation, data curation, formal analysis, investigation,
887 methodology, visualisation and writing the original draft, reviewing and editing previous versions of the
888 current manuscript; CH contributed to conceptualisation, data collection, data curation, funding acquisition,
889 investigation, methodology, reviewing and editing earlier versions of the manuscript; CH contributed to the
890 data annotations, investigation and methodology, reviewing and editing earlier versions of the manuscript;
891 SR contributed to conceptualisation and participant recruitment, reviewing and editing earlier versions of the
892 manuscript; RB contributed to the conceptualisation, investigation, methodology, funding acquisition and
893 reviewing and editing earlier versions of the manuscript; LL contributed to methodology, formal analysis
894 and reviewing and editing earlier versions of the manuscript; DS contribute to the conceptualisation, data
895 collection, data curation, formal analysis, funding acquisition, investigation, methodology, project
896 administration, resources, supervision, validation, writing the original draft, reviewing and editing previous
897 versions of the current manuscript.

898

899

900

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1374

1375 **Appendices**: A supplemental file is available, containing detailed demographic information of the participants, as well as additional analyses (e.g., acoustic features, lexical diversity, and parts of
1377 speech). It also includes the dialogue act classification used in the study, with illustrative examples, and

1378 a table that schematically summarizes previous research on pragmatic abilities in Deaf and Hard of

1379 Hearing children.

1380

1381

1382 **Caption Figure 1**

1383 Figure 1: Proportional Duration of Tasks for each Child (one per row) by Group. The game comprised 9

1384 tasks: 5 main Map Tasks (MT1-5) and 4 Sub-Tasks (ST1-4). Each colour represents one task, if one row

1385 misses any colour it means that the tasks have not been completed in the allocated time (ca. 30 mins). In the

1386 DHH group (top), one can see that 4 dyads do not manage to complete the last 2 Tasks (ST-4 & MT-5).

1387

1388 **Caption Figure 2**

1389 Figure 2: Convergence over Turns by Group (DHH and TH) and Role (Adult and Child)

1390 (a) Syllable Rate Convergence

1391 (b) Mean F0 Convergence

1392 (c) Mean Intensity Convergence

1393

1394 **Caption Figure 3**

1395 Figure 3: Speaking times and Turn dynamics by Role (Adult and Child) and Group (DHH/TH)

1396 (a) Balance

1397 (b) Duration turns

1398 (c) Turns within

1399 (d) Turn transitions

1400

1401 **Caption Figure 4**

1402 Figure 4: Dialogue Acts (DAs) Production and Responsivity in Children by Group (DHH and TH)

1403 (a) Mean percentages of DAs types initiated by Children
1404 (b) Percentages of random guessing

1405 (c) Percentage of failure in responding to DAs initiated by the Adult

1406

1407 **Caption Figure 5**

1408 Figure 5: Laughter, Speech-laughter and Laughter Mimicry distributions according to Group and Role.

1409 (a) Mean Laughter (L) and Speech-laughter (SL) occurrences

1410 (b) Percentages of Laughter Mimicry.

1411 (c) Transitional Probabilities of Laughter Mimicry