Dynamics of pupil response during the Sentence-final Word Identification and Recall test
Elaine Hoi Ning Ng1,2,*, Sindri Jonsson1, Emil Bjergskov Larsen1, Torben Christiansen3, Andreea Micula1,21Oticon A/S, Smørum, Denmark 2Department of Behavioural Sciences and Learning, Linköping University, Sweden 3EPOS A/S, Ballerup, Denmark
Introduction
There is a growing interest in learning how listening effort and memory effort areinvested during speech understanding. One way to investigate the effort investment isto compare the pupil responses during a speech recognition task that requires recall.
Previous studies suggested that baseline pupil dilation increases when speech recall isrequired in the task (Bönitz et al., 2021), as well as better overall recall performancesuggesting higher memory effort due to speech encoding (see poster More is more:
Physiological markers of successful effort by Micula et al. presented in this conference).
Increase in task-evoked (peak and mean) pupil responses is believed to be associated withincreased listening effort.

Results1) SWIR performance Word identification performance with noise attenuation (mean 99.7%, SD 1.0%) was
significantly better than without (mean 96.2%, SD 5.8%) (p < 0.01).
 Figure 1 shows the recall performance as a function of word position. When the average recall
performance was calculated based on the total number of to-be-recalled words in a list (i.e. 7words), the performance was significantly better with noise attenuation (mean 73.2%, SD13.4%) than without (mean 68.8%, SD 12.1%) (p < 0.05).

IHCON 2022

 For each trial (sentence), we extracted two features: sentence baseline and mean
pupil dilation. We applied linear fits to the data points across a list (7 points) for
each feature. The slopes fits of sentence baseline and mean pupil dilation werethen obtained for each participant (Bönitz et al., 2021).
 Baseline slope indicates the modulation of memory effort throughout the list
 Mean pupil dilation slope indicates the dynamic change in listening effort

 Noise attenuation siginificantly increased the slope fits of baseline (Figure 3) andreduced the slope fits of mean pupil dilation (Figure 4).

 However, when the average performance was calculated based on the total number of word
identified (i.e. word identification performance), the difference in performance between
conditions became insignificant (p = 0.14).

Noise attenuation technology in hearing solutions can enhance recall performance byfreeing up cognitive resources for speech recall (Ng et al., 2013, 2015). However, somerecent investigations done among people with normal hearing and hearing loss using
the combination of pupillometry and a speech recall task reported mixed results interms of changes in baseline and task-evoked pupil responses.
Aim: To better understand the effect of noise attenuating technology on the dynamics
of pupil responses during a speech recall task, we examined the effect of apreprocessed noise attenuation technology on recall performance and pupil responses.

Figure 3. Increased slope fits of baseline dilation with noise
attenuation than without.
Figure 1. Average recall performance as afunction of word position in a 7-sentence
list. Solid lines represent recall
performance calculated based on 7 finalwords. Dotted lines represent recall
performance calculated based on the word
identification performance.

Methods
 Nineteen adults (8 female) with self-reported normal hearing aged between 22 and 53 years(mean age 36 years, SD 10) were included in the analyses.
Sentence-final Word Identification and Recall test (SWIR) was administered (Ng et al., 2013)
Tasks: 1) identify and verbally repeat the final word after listening to each sentence, and 2)
recall all final words when a list finishes.
Test conditions: with and without noise attenuation. All sentence-in-noise stimuli werepreprocessed.

Figure 4. Decreased slope fits of mean pupil dilation with noise
attenuation than without.

Discussions
 Speech recall performance was better in the condition when noise attenuation
was applied. At the same time, there was a stronger increase in baseline pupil
dilation over the course of a SWIR list, indicating higher memory effort.
 A stronger decrease in the mean pupil dilation with noise attenuation, suggests
less listening effort throughout a list.

2) Pupil responses
 Figure 2 shows the aggregated pupil traces obtained across all participants.

For each condition, 7 lists of 7 sentences were presented in the a 4-talker babble noise.
Sentence stimuli and noise were fixed at 69 and 70 dB SPL respectively.

 These findings suggest that reduced listening effort liberates cognitive resourcesthat can be used for speech processing and encoding of speech information into
long-term memory (cf. Micula et al.). This can lead to better recall performance.
 The dynamics of the pupil responses also support the notion that working memory
is a limited capacity.
w/o Noise Attenuation

Pupil responses:Noise Attenuation

Sentence baseline: State of arousal (including memory effort)
Mean Pupil Dilation: Listening effort
List Sentence Mean pupil
dilationbaseline baseline
Figure 2. Pupil traces aggregated within trial (sentence) x conditions across participants. The aggregated pupil traces are relative to the list
baseline. The shaded area indicates standard error.

* Contact: ehon@oticon.com

References

Acknowledgement

Bönitz et al. (2021). Ear Hear, 42(4), 846-859.
Ng et al. (2013). Int J Audiol, 52(7), 433-41.
Ng et al. (2015). Ear Hear, 36(1), 82-91.

This study is funded by EPOS A/S.