Age-related deficits in dip-listening evident for isolated sentences but not for spoken stories

Irsik, Vanessa C.; Johnsrude, Ingrid S.; Herrmann, Björn

doi:10.1038/s41598-022-09805-6

Cited by 14 publications

(26 citation statements)

References 121 publications

(176 reference statements)

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“…Overall, 19.7% of datasets, i.e., 29 out of 147 participants, were excluded. Removal of ~20% of datasets is in line with previous online work that involved comparable screening protocols (Irsik et al, 2022;Herrmann, 2023b).…”

Section: Participantssupporting

confidence: 65%

Impaired prosodic processing but not hearing function is associated with reduced recognition of AI speech in older adults

Herrmann,

Cui

2024

Preprint

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Voice artificial intelligence (AI) technology becomes increasingly common in everyday life, for example, in automated phone services, voice assistive systems (e.g., Siri), and social chat bots. However, most research has focused on how younger adults perceive modern AI speech, leaving the development of this technology age-uninformed. Recent work indicates that older adults are less able to identify modern AI speech compared to younger adults, but the underlying causes are unclear. The current study with younger (N=133; 22-39 years) and older adults (N=146; 54-79 years) investigated potential factors that could explain the age-related reduction in AI speech identification. In Experiment 1, we investigated whether high-frequency information in speech – to which older adults have less access due to hearing loss – contributes to age-group differences, but our results showed that older adults were less able to identify AI speech for both full-bandwidth speech and speech for which information above 4 kHz was removed. This result makes the contribution of hearing loss less likely. In Experiment 2, we investigated whether the known age-related reduction in the ability to process prosodic information in speech predicts the reduction in AI speech identification. Indeed, the ability to identify AI speech was greater in individuals who also showed a greater ability to identify emotions from prosodic speech information, after accounting for hearing function and self-rated experience with voice AI systems. The current results suggest that the ability to identify AI speech is related to the accurate processing of prosodic information.

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Section: Participantssupporting

confidence: 65%

Impaired prosodic processing but not hearing function is associated with reduced recognition of AI speech in older adults

Herrmann,

Cui

2024

Preprint

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“…Each story was masked by 12-talker background babble (Bilger, 1984). The SNR between the speech signal and the 12-talker babble changed every 28 seconds to one of five SNR levels (+16, +11, +6, +1, −4 dB SNR; for a similar approach see Irsik et al, 2022a, b), corresponding to about a range of 95% to 50% of intelligible words (Irsik et al, 2022a). The SNR was manipulated by adjusting the dB level of both the story and the masker.…”

Section: Methodsmentioning

confidence: 99%

Eye movements decrease during effortful speech listening

Cui¹,

Herrmann²

2023

Preprint

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Pupillometry is the most used objective tool to assess listening effort but has several disadvantages. The current study explores a new, objective way to assess listening effort through eye movements. Building on cognitive and neurophysiological work, we examine the hypothesis that eye movements decrease when speech listening becomes challenging. In three experiments with human participants from both sexes, we demonstrate, consistent with this hypothesis, that fixation duration increases and spatial gaze dispersion decreases with increasing speech masking. Eye movements decreased during effortful speech listening for different visual scenes (free viewing; object tracking) and speech materials (simple sentences; naturalistic stories). In contrast, pupillometry was insensitive to speech masking during story listening, highlighting the challenges with pupillometric measures for the assessments of listening effort in naturalistic speech-listening paradigms. Our results reveal a critical link between eye movements and cognitive load, and provide the foundation for a novel measure of listening effort applicable in a wide range of contexts.

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“…Engagement measured neurally through across-participant synchronization of neural activity also appears to be little affected by moderate background masking (Irsik et al, 2022a). Moreover, older adults appear to benefit from speech glimpses in background noise for comprehension more when listening to spoken stories than when listening to disconnected sentences (Irsik et al, 2022b). This suggests that something about the stories – perhaps the degree to which they pique interest and motivate listening?…”

Section: Introductionmentioning

confidence: 99%

The Effects of Speech Masking on Neural Tracking of Acoustic and Semantic Features of Natural Speech

Yasmin¹,

Irsik²,

Johnsrude³

et al. 2023

Preprint

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Listening environments contain background sounds that mask speech and lead to communication challenges. Sensitivity to slow acoustic fluctuations in speech can help segregate speech from background noise. Semantic context can also facilitate speech perception in noise, for example, by enabling prediction of upcoming words. However, not much is known about how different degrees of background masking affect the neural processing of acoustic and semantic features during naturalistic speech listening. In the current electroencephalography (EEG) study, participants listened to engaging, spoken stories masked at different levels of multi-talker babble to investigate how neural activity in response to acoustic and semantic features changes with acoustic challenges, and how such effects relate to speech intelligibility. The pattern of neural response amplitudes associated with both acoustic and semantic speech features across masking levels was U-shaped, such that amplitudes were largest for moderate masking levels. This U-shape may be due to increased attentional focus when speech comprehension is challenging, but manageable. The latency of the neural responses increased linearly with increasing background masking, and neural latency change associated with acoustic processing most closely mirrored the changes in speech intelligibility. Finally, tracking responses related to semantic dissimilarity remained robust until severe speech masking (-3 dB SNR). The current study reveals that neural responses to acoustic features are highly sensitive to background masking and decreasing speech intelligibility, whereas neural responses to semantic features are relatively robust, suggesting that individuals track the meaning of the story well even in moderate background sound.

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Age-related deficits in dip-listening evident for isolated sentences but not for spoken stories

Cited by 14 publications

References 121 publications

Impaired prosodic processing but not hearing function is associated with reduced recognition of AI speech in older adults

Impaired prosodic processing but not hearing function is associated with reduced recognition of AI speech in older adults

Eye movements decrease during effortful speech listening

The Effects of Speech Masking on Neural Tracking of Acoustic and Semantic Features of Natural Speech

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