Pupil Dilation Is Sensitive to Semantic Ambiguity and Acoustic Degradation

Abstract

Speech comprehension is challenged by background noise, acoustic interference, and linguistic factors, such as the presence of words with more than one meaning (homonyms and homophones). Previous work suggests that homophony in spoken language increases cognitive demand. Here, we measured pupil dilation—a physiological index of cognitive demand—while listeners heard high-ambiguity sentences, containing words with more than one meaning, or well-matched low-ambiguity sentences without ambiguous words. This semantic-ambiguity manipulation was crossed with an acoustic manipulation in two experiments. In Experiment 1, sentences were masked with 30-talker babble at 0 and +6 dB signal-to-noise ratio (SNR), and in Experiment 2, sentences were heard with or without a pink noise masker at –2 dB SNR. Speech comprehension was measured by asking listeners to judge the semantic relatedness of a visual probe word to the previous sentence. In both experiments, comprehension was lower for high- than for low-ambiguity sentences when SNRs were low. Pupils dilated more when sentences included ambiguous words, even when no noise was added (Experiment 2). Pupil also dilated more when SNRs were low. The effect of masking was larger than the effect of ambiguity for performance and pupil responses. This work demonstrates that the presence of homophones, a condition that is ubiquitous in natural language, increases cognitive demand and reduces intelligibility of speech heard with a noisy background.

Neural alpha oscillations and pupil size differentially index cognitive demand under competing audio-visual task conditions

“…Pupil size tracks cognitive demand in the auditory and visual tasks Pupil size increased with the degree of cognitive demand for both the auditory and the visual task (Figure 3). This increase in pupil size with cognitive demand is generally consistent with previous work (Kadem et al, 2020;Kahneman & Beatty, 1966;Koelewijn et al, 2012;Martin et al, 2020;Ohlenforst et al, 2018;Porter et al, 2007;Stolte et al, 2020;Wendt et al, 2016;Winn et al, 2018;Zekveld et al, 2010;Zekveld & Kramer, 2014;Zhao et al, 2019).…”

“…Pupil size variations are mainly driven via noradrenergic pathways from Locus Coeruleus (Aston-Jones & Cohen, 2005; Joshi et al, 2016; Joshi & Gold, 2020) that is modulated by attention (Vazey et al, 2018) or arousal (Breton-Provencher & Sur, 2019; Murphy et al, 2011). Pupil size is long known to vary with the degree to which a person engages cognitively in a task (Kahneman & Beatty, 1966) and has recently gained substantial interest especially in the hearing sciences, as a potential indicator of listening effort: pupil size increases with increasing speech-comprehension difficulty induced by acoustic degradation (Miles et al, 2017; Winn et al, 2016), acoustic masking (Koelewijn et al, 2012; Zekveld et al, 2010), or linguistic complexity (Kadem et al, 2020; Wendt et al, 2016). Apart from the sensitivity of pupil size to auditory-related demands, pupil size further increases with the degree of cognitive demand during visual stimulation (Martin et al, 2020; Porter et al, 2007; Stolte et al, 2020) and memory performance (Kahneman & Beatty, 1966; Miller et al, 2019).…”

Eye movements decrease during effortful speech listening

“…After each stimulus, a probe word occurred on the screen. Participants were asked to indicate whether the probe word is semantically related or unrelated to the sentence (Rodd et al, 2010a;Rodd et al, 2010b;Kadem et al, Participants were presented with six blocks of stimulation. In three blocks, participants were presented with the blank screen (free viewing), whereas in the other three blocks, participants were presented with the fixation square.…”

Learning about the meanings of ambiguous words: evidence from a word-meaning priming paradigm with short narratives

“…In spoken language, a similar increase in processing time and resources for ambiguous compared to unambiguous words has been shown in studies using a range of approaches including neuroimaging ( e.g. , Rodd, Davis & Johnsrude, 2005 ; see Vitello, 2014 for review), dual-task methods ( Rodd, Johnsrude & Davis, 2010 ), picture selection tasks ( Foss, Bever & Silver, 1968 ) and pupillometry ( Kadem et al, 2020 ).…”