PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Speech comprehension and intelligibility in noise in 11 to 13 years
old children: what is the relationship?
Nicola PRODI1; Chiara VISENTIN2; Erika BORELLA3;
Irene MAMMARELLA4; Alberto DI DOMENICO5
1,2
3
4
5

Department of Engineering, University of Ferrara, Italy

Department of General Psychology, University of Padova, Italy

Department of Developmental and Social Psychology, University of Padova, Italy

Department of Psychological, Health and Territorial Sciences, University of Chieti, Italy

ABSTRACTIn classrooms, the correct reception of what the teacher says is a necessary condition for learning, but it is not
sufficient to ensure that the content of the message is understood. Notwithstanding this, usually a direct
positive correlation between the performance in speech reception and sentence comprehension (SC) is
assumed. In fact, this idea is the ground for the use of speech intelligibility (SI) in the design of learningspaces. In this study, the relationship between SC and SI is investigated in three listening conditions, withreference to 159 school-age children, aged 11 to 13 years old, with normal hearing. Participants completed
two tasks designed and validated to measure SI and SC, which were presented in three conditions: quiet,
classroom noise and road traffic noise. The tasks were presented to groups of children within their classrooms,
via tablet and loudspeakers, within a one-hour session. For each task, results in quiet were compared to theresults in noise, assessing the specific effect of each masker; furthermore, the presence of an interaction
between noise type and task type was investigated to gain insight on the relation between the two tasks.
Keywords: classroom acoustics, sentence comprehension, intelligibility

1. INTRODUCTION
For children in classrooms, the ability of hearing what the teacher says is critical for success inacademic activities. However, the correct reception of the spoken message it is not sufficie nt to ensurethat the content of the message is understood (1). Currently, all the standards in classroom acoustics
are conceived to guarantee speech intelligibility (SI) only. The standards provide limits in terms ofacoustical indicators, which are designed to account for the separate and/or joint effects of noise androom reverberation on speech reception. Unfortunately, SI is at the surface of the levels ofrepresentation involved in verbal processing (2), and it is mainly informative on the correct receptionof the acoustic-phonetic cues of the message. Even though a variety of test have developed to evaluate
SI, relying on progressively more cognitive demanding material (from isolated words, to unpredictablesentences), they are not able to capture the higher level language processing required incommunication during lessons. Indeed, the latter relies on messages with variable syntactical forms,
lexical, semantic and contextual information, and the listeners are expected not only to understand thecontent, but also to make inferences based on their previous knowledge.
In order to improve assessments based only on SI, a viable alternative is the usage of sentencecomprehension (SC). This task provides information on levels of language processing beyond s peech
reception, since auditory, syntactic, contextual and semantic information can be manipulated in a1

nicola.prodi@unife.it
chiara.visentin@unife.it
3 erika.borella@unipd.it
4 irene.mammarella@unipd.it
5 alberto.didomenico@unich.it
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simple and scalable manner (3). The comparison of the two tasks (SI and SC) have not beensystematically examined, whereas some results are available for the comparison of SI and some more
complex tasks of listening comprehension (4, 5). Overall, literature results point toward a poor relation
between performance in speech intelligibility and comprehension tasks. The relation should be moreclosely investigated aiming at providing effective tools for the control of noise and reverberation in theclassroom.
Reasons for the specific impact of noise and reverberation on the outcomes of verbal tasks inclassrooms have also been formulated. In particular, it was found that the interference of noise on
speech depends not only on the noise level, but also on its spectro -temporal characteristics. Thechanging state character of an unintelligible speech-like masker affects high level cognitive
processing in both children and adults, due to the interference with the to -be-remembered material (6).
Furthermore, most of the available results related to speech processing of children in the classroom
are based on their task performance, whereas only a few take into consideration their listening effort
by using the behavioral measure of response time (7-9). Considering listening effort beside
performance would allow depicting a more comprehensive view of both perceptual and cognitive
processing that children implement to cope with listening in noisy classrooms.
The present study investigates SI and SC in real reverberating classrooms, using standardized test.
Middle-school students were presented with the tasks in a closed-set format, by using portable devices(tablets). Three listening conditions were presented: quiet, traffic noise, classroom noise. Twooutcome measures were considered (task performance and response time), and used to develop acomprehensive view of the speech processing phenomenon.

2.

METHODS

2.1 Participants
A total of 159 students participated in the study, from nine classes (three for each grade) of two
middle-schools located in Ferrara (Italy): 53 11-year-olds (33%), 49 12-year-olds (31%) and 57
13-year-olds (36%).
2.2 Experimental design
Participants completed the two tasks in the three listening conditions in one session, during themorning school-hours. An assessment of the students’ reading comprehension in quiet was carried out
in a separate session, one week after the experiment. The order of the tasks and the order of thelistening conditions within each task was balanced across the classes of each age group . The three test
lists used for each task were pseudo-randomized, in order to avoid the matching of the same test list
with the same listening condition.
2.3 Laboratory classrooms
The experimental session took place in two laboratory classrooms, one for each school. Bothclassroom were box-shaped and had a similar volume of 155 m 3. In order to make the acoustic
conditions of the two classrooms as similar as possible, one of the two spaces was equipped with soundabsorbing polyester fiber blankets. The temporary acoustic treatment ensured that the difference in thereverberation time of the two classrooms was smaller than the just-noticeable difference defined in the
ISO 3382 standard (10).
During the test sessions, the classrooms were setup as for regular lessons (desks and chairsarranged in regular lines and facing the teacher’s desk). A Gras 44AB mouth simulator was placed
close to the teacher’s desk, at a height of 1.5 m, and used for the playback of the speech signals.
Furthermore, a Look Line D203 omnidirectional source placed on the floor, close to one of the room
corners, and used for the playback of the background noises.
2.4 Speech intelligibility task
Speech intelligibility was assessed by using the Matrix Sentence Test in the Italian language ( 11,ITAMatrix). In each trial a five-word sentence was orally presented. The sentence had a fixed syntactic
structure but no semantical predictability (e.g., “Mary draw five little boxes”); it waspseudo-randomly generated from a 10x5 base-word matrix. After the sentence playback, thebase-word matrix was presented to the participants; their task was to select the words they heard inserial order. Each trial was time-limited to 15 s.

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Participants were presented with a total of 48 sentences (16 for each listening conditions); the threelistening conditions were presented in a blocked fashion. For each sentence, speech intelligibility(percentage of correct words identified within the sentence) and response times (RTs) were recorded.
The latter quantity was defined as the time elapsed between the audio offset and the selection of thefirst word on the tablet.
2.5 Sentence comprehension task
Sentence comprehension was evaluated by using the COMPRENDO test ( 12). The test consists ofmeaningful sentences in the Italian language, which differ in their syntactic complexity (e.g., “Themother is chasing the child” or “The child looks at the cat and the mother pets the dog”). The sentenceswere recorded by an adult, native Italian female speaker in a silent room. Afterwards, the sentenceswere digitally filtered to match the long-term spectrum of the female speaker of the ITAMatrix.
During the experiment, the sentences were orally presented to the participants. After the audio
offset, a set of four images appeared on the tablet and the participants were asked to select the image
that properly described the sentence they just heard. Each trial was time -limited to 12 s. Sixteen
sentences were presented for each listening condition, and for each trial accuracy and response time
were recorded.
2.6 Listening conditions
The tasks were presented in three listening conditions: quiet, road traffic noise and classroom noi se.
In all conditions the speech signal was fixed to a level of 63 dB(A), measured at 1 m in front of themouth simulator; this correspond to a talker speaking with a vocal effort intermediate between “normal”
and “raised” (13).
In the quiet condition the tasks were presented in the ambient noise of the classrooms, primarily
made up by noises coming from the adjacent classrooms. In the traffic condition, recordings of a busy
road in conditions of dense traffic were played back. The classroom noise consisted an unintelligible
fluctuating masker mixed with sound events typical of a working classroom (pen drops, turning over ofbook pages…). The fluctuating masker was obtained by processing Italian phrases, spoken by a native
female speaker, according to the established ICRA procedure (14).
The background noises were played back at a level of 60 dB(A), measured at the audience position.
The noise level was chosen to be intermediate between the maximum and the minimum levels (70 and
50 dB(A), respectively) measured in working secondary-school classrooms (15).
The objective description of the listening conditions during the experiment was achieved bymeasuring the reverberation time and the long-term levels of the ambient noise, the speech signal, andthe added background noises (reproduced as during the tests) at the end of the experiment, within theoccupied classroom. The listening conditions are summarized in Table 1. It is worth noticing that thedifference between the listening conditions in the two classrooms are always smaller than the JND for
all the acoustic parameters. Then, the two classrooms can be considered as almost equivalent from thepoint of view of acoustical perception, and their results will be considered together henceforth.
Table 1 – Listening conditions in the two classrooms during the experiment (occupied conditions):
reverberation time Tmid (average across the 500–2000 Hz octave bands), A-weighted sound pressure level,sound-to-noise ratio (SNR).
Acoustic parameterclassroom Aclassroom B

Tmid [s]

0.68

0.69

speech signal level dB(A)

60.4

59.5

SNR – quiet (dB)

17.1

19.0

SNR – traffic (dB)

-0.5

-0.4

SNR – classroom noise (dB)

-0.1

0.6

2.7 Procedures
The participants were collectively presented with the test session. They were divided in groups

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composed by the whole class, which took turns in the laboratory classroom.
Upon entering the classroom, each child was given a tablet and randomly assigned to a seating
position. Afterwards the participants were briefly informed on the study aim, and started the test
session. Prior to each task, verbal instructions were given to the participants, which were alsofamiliarized with the task and the data collection system by presenting a set of four trials in quiet.
In the noisy listening conditions, the noise playback started approximately one second before thesentence and ended simultaneously to the signal. Each experimental trial was time-limited, and only
when all participants had responded or reached the time out, the next sentence was played backautomatically.
The whole experiment was managed by using a wireless test bench (9), based on a server
application which simultaneously controlled the audio playback, the presentation of thebase-matrix/images on the tablets and the data collection.
2.8 Data analysis
Statistical analyses were performed using generalized mixed-effects models (GLMMs), selected todeal with the repeated-measures design and the lack of normality in the distribution of the dependent
variables.
The software R was used for the analysis (packages: lme4, lsmeans), with a significance level of
0.05. A GLMM with a binomial distribution was used to analyze the accuracy data (SI or percentage
correct), whereas a Gamma distribution with a log-link function was selected for the RTs. The variable
participant was included as a random intercept and the within -subject factor listening condition was
included in the random effects as a random slope. Furthermore, the score in the reading comprehension
task was entered in the models as a covariate. When appropriate, planned pairwise comparisons were
performed, correcting for the test multiplicity using a Bonferroni procedure.
Prior to data analysis, missing data points due to technical errors or out-of-times were removed
from the databases (7.1% for the SI task, 1.4% for the SC task).

3. RESULTS
3.1 Effects of listening condition of task performance
Two GLMMs were set up, one for each task, with performance as the dependent variable; listening
condition was included as a fixed factor. Figure 1 displays the performance as a function of listening
condition, for the two tasks.

Figure 1 – Mean performance (SD) as a function of the listening condition for the two tasks: speech
intelligibility (left panel), sentence comprehension (right panel). *p < 0.05; ** p < 0.01; *** p <0.001
For the speech intelligibility task, analysis revealed a significant main effect of listening condition(χ 2(2)=189.23, p<0.001). Post hoc tests indicated that performance significantly decreased in noisy
compared to quiet condition, and in classroom noise compared to traffic (p<0.001 for all comparisons).
The performance decrease in traffic compared to quiet was equal to 1.6%; in classroom noise
performance decreased of an additional 5.5%.
For the sentence comprehension task the effect of listening condition was significant as well5947

(χ 2(2)=8.30, p=0.016). Post hoc pairwise comparisons revealed that the probability of a correct
response was significantly higher in quiet compared to classroom noise (p=0.016); the task
performance decreased in classroom noise versus quiet by 2.2%.
3.2
Effects of listening condition of response time
Two GLMMs were set up, one for each task, with RT as the dependent variable; listening condition
was included as a fixed factor. Figure 2 displays the RT as a function of listening condition, for the twotasks.
For the speech intelligibility task, analysis revealed a significant main effect of listening condition(χ 2(2)=22.63, p<0.001). Post hoc tests indicated that RTs significantly slowed down in classroom noisecompared to quiet and traffic (p<0.001 and p=0.002, respectively). The mean ratio (ratio of the mean
RT in classroom noise to RT in another condition) was 0.92 with reference to quiet and 0.95 withreference to traffic.
For the sentence comprehension task the effect of listening condition was significant as well(χ 2(2)=30.60, p<0.001). Post hoc pairwise comparisons revealed that RTs significantly slowed down inclassroom noise compared to quiet and traffic (p<0.001 for both comparisons); no significant
difference was found in the RTs of the two noisy conditions. The mean ratio was 0.92 with reference toquiet, and 0.93 with reference to the traffic condition.

Figure 2 – Mean response times (SD) as a function of the listening condition for the two tasks: speech
intelligibility (left panel), sentence comprehension (right panel). *p < 0.05; ** p < 0.01; *** p <0.001
3.3 Comparison of the effect of noise on the two tasks
In order to compare directly the effects of noisy conditions on performance and RTs of the two task,
the relative change in noise compared to quiet was considered.
The change in performance was quantified by the ratio of the task performance in noise to the task
performance in quiet. Therefore, the quiet condition has a value equal to the unity for allparticipants-task combinations, and smaller values denote decreased performance compared with thequiet condition. Concerning RTs, the normalization was defined by the ratio of the median RT in noise
to the median RT in quiet, for each task. For this variable, values greater than one reveal increased
listening effort compared with quiet. The normalized results are presented in Figure 3, as a function of
the noisy listening conditions.
The statistical analysis was carried out with two LMMs (one for each dependent variable). The
models included listening condition (traffic and classroom; as quiet was one by definition it was notincluded in the model), task (speech intelligibility, sentence comprehension), and their two-way
interaction as fixed factors. The score in the reading comprehension task was added to the models as acovariate; a random intercept (participant) and two random slopes (the within -participant variables
listening condition and task) were also specified.

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Figure 3 – Accuracy scores (left) and response times (right) relative to the quiet condition, as a function of thetask and the noise type. *p < 0.05; ** p < 0.01; *** p <0.001
Concerning the normalized performance, analysis indicated a significant effect of listening
condition (χ 2 (2)=59.33, p<0.001) and task (χ 2 (1)=18.18, p<0.001), and a significant interaction
between the two factors as well (χ 2(2)=23.93, p<0.001). The pairwise comparisons between the tasks
for each listening condition revealed a significant difference between the tasks only in classroom noise(p<0.001); no difference was found in traffic. When the effect of listening condition was considered
for each task, the pairwise comparisons revealed that in both tasks the performance decrease wasgreater in classroom noise versus traffic (speech comprehension: p=0.007; sentence comprehension:p<0.001).
Concerning the normalized response times, the analysis indicated a significant ma in effect oflistening condition (χ 2 (1)=29.34, p<0.001), with higher normalized results in the classroom noise
condition compared to traffic. The main effect of task and the two-way interaction were notsignificant.

4. DISCUSSION
4.1 Effects of listening condition
For both tasks and dependent variables, a significant main effect of listening condition was found,indicating that the addition of a background noise at a level typical of a working classroom generally
decreased the pupils’ performance and slowed down the RTs compared to quiet.
When considering performance in the SI task, all listening conditions could be distinguished:classroom noise disrupted intelligibility significantly more than traffic, which in turn was more
impairing than quiet. Differently, in the SC task, only a significant decrease in classroom noise versus
quiet was be found, whereas performance in traffic was not significantly different from performance inquiet. This finding could be related to a ceiling effect observed in the accuracy of the task, with results
higher than 95% for all listening conditions. The effect can be traced back to the additional cues thatthe pictorial representation of the actions provided and that supported the listeners in coping with thetask. As expected, the classroom noise impaired performance in the two tasks more than traffic, due toits changing-state nature. In addition to this domain-specific interference, the effect of the classroom
noise may also be related to a capture of attention. In fact, salient soun d events (as the pen dropping,chair scratching events mixed to the ICRA signal) additionally impair the performance by capturing
the listener’s attention (16).
Concerning the effects of listening conditions on RTs, it was found that in both tasks the res ponse
latencies were longer in classroom noise compared with both quiet and traffic. In this study RTs wasconsidered as a proxy of listening effort, with slower RTs indicating increased effort . The longer
latencies in classroom noise, mirroring the performance decrease, indicated that more use of cognitive
resources is needed for processing the auditory information in degraded listening conditions; thisresults in fewer resources available for the task and in turn in a poorer performance.
Differently, the absence of significant differences between the other two listening conditions5949

suggests that the 11-13 years children were able to cope successfully with the traffic noise, which did
not impair listening effort in comparison with quiet. The finding is in line with previous studies thatused response time as a proxy for listening effort for primary school students (9, 17) and indicated thateven when background noises have the same SNR with respect to the teacher’s voice, the difference intheir spectral content may lead to an additional cognitive load.
4.2 Speech intelligibility versus sentence comprehension
This work addressed the relation between SI and SC using a standardized audiological test for SI
and a standardized test battery for SC. The tools were designed to respond to cognitive mechanismsthat do not match. In the SC tasks listeners are required to create a global picture of the sentence
meaning by integrating lexical, semantic and syntactic information. Differently, the SI task requires torecognize and to recall all the words of the sentence, without any support from the context or from thefixed syntactic structure. Therefore, the absolute results of the two tasks were not directly comparedand instead changes relative to quiet were considered.
Concerning performance, the analysis indicated a significant interaction between noise and task,suggesting that classroom noise had a greater impact on SI compared to SC. The finding is in line withprevious studies, suggesting that the two tasks are differently impacted by the background noise level(4) and by the spectro-temporal characteristics of the masker (5). Overall, the findings suggest that
directly transposing the results obtained in SI (in quiet or in noise) to SC might not be meaningful andthus acoustical conditions that guarantee optimal intelligibility might not be equally adequate forspeech comprehension.
Concerning RTs, no significant interaction was found between noise and task thus suggesting thatthe increase of listening effort due to the presence of classroom noise did not depend on the type of task.
However, further analyses are needed to get a deeper insight on the relation, which for instance may be
influenced by developmental effects (e.g., age of the students).
Even though research on the topic is still scarce, the current results seem to suggest that the link
between the SI and the SC tasks cannot be captured by a simple relationship, which is instead strongly
influenced by the specific characteristics of the tasks themselve s. For instance, it was found that thevisual, closed-set format of the SC task selected greatly supported the listeners in solving the task andmade SC comparatively easier than SI. The near-ceiling results prevented a direct comparison of SC
and SI performance, so that it was not possible to draw a meaningful relationship between the twotasks. However, given the interactions pointed out by the analysis on the normalized quantities, it isbelieved that a more extensive investigation of the relationship wo uld be of interest.

5. CONCLUSIONSIn this study, speech intelligibility and sentence comprehension in 11 to 13 -year-olds were
investigated under three listening conditions (quiet, traffic, classroom noise), aiming at better
understanding the effects of background noise, and the relationship between the two tasks. The
following results were found:(1) A background noise with changing state characteristics was detrimental to the performance of
11 to 13-year-olds in both tasks; the effect was also mirrored by listening effort, as witnessed by aslowing down of the RTs. Differently, the children were able to cope successfully with the traffic noise,
which did not impair listening effort in comparison with quiet.
(2) Classroom noise impaired more SI than SC but a clear relationship between the two tasks could
not be derived, since several factors, such as the character of the noise and task details appear tomodulate the relation between the two tasks. Further investigations are warranted to explore therelation over a wider range of SNR and noise types.

ACKNOWLEDGEMENTS
The authors would like to thank the schools, the children and the teachers who took part in the study.
In addition, the authors acknowledge Hörtech GmbH, Oldenburg (D), for providing the speechrecordings of the Matrix Sentence Test in the Italian language, and Cristiana Erbi, who administeredand scored the reading comprehension test.

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