Impact of Background Noise and Sentence Complexity on Processing Demands during Sentence Comprehension

Abstract

Speech comprehension in adverse listening conditions can be effortful even when speech is fully intelligible. Acoustical distortions typically make speech comprehension more effortful, but effort also depends on linguistic aspects of the speech signal, such as its syntactic complexity. In the present study, pupil dilations, and subjective effort ratings were recorded in 20 normal-hearing participants while performing a sentence comprehension task. The sentences were either syntactically simple (subjectfirst sentence structure) or complex (object-first sentence structure) and were presented in two levels of background noise both corresponding to high intelligibility. A digit span and a reading span test were used to assess individual differences in the participants' working memory capacity (WMC). The results showed that the subjectively rated effort was mostly affected by the noise level and less by syntactic complexity. Conversely, pupil dilations increased with syntactic complexity but only showed a small effect of the noise level. Participants with higher WMC showed increased pupil responses in the higher-level noise condition but rated sentence comprehension as being less effortful compared to participants with lower WMC. Overall, the results demonstrate that pupil dilations and subjectively rated effort represent different aspects of effort. Furthermore, the results indicate that effort can vary in situations with high speech intelligibility.

Effort Not Speed Characterizes Comprehension of Spoken Sentences by Older Adults with Mild Hearing Impairment

“…During a blink or semi-blink the ratio quickly drops toward 0. All samples with a ratio differing more than 1 SD from the mean were eliminated (Piquado et al, 2010; see also Zekveld et al, 2010; Kuchinsky et al, 2014; Winn et al, 2015; Wendt et al, 2016). …”

“…Pupil sizes were additionally adjusted to account for any trial-to-trial variability in pupil diameter (Kuchinsky et al, 2013; Wendt et al, 2016), using a baseline of the mean pupil diameter during a 2-s pre-sentence silence as the d min in the above equation and the maximum post-sentence pupil diameter as the d max .…”

“…At the behavioral level, however, increases in pupil size relative to baseline have been shown to serve as a reliable index of effortful processing, whether in response to listening effort attendant to a degraded speech signal (Zekveld et al, 2011; Kuchinsky et al, 2013; Zekveld and Kramer, 2014; Wendt et al, 2016), to increasing cognitive load in problem-solving and memory tasks (Hess and Polt, 1964; Kahneman and Beatty, 1966; Beatty, 1982) or recall of sentences that increase in length and syntactic complexity (Piquado et al, 2010). …”

Cortical oscillations and entrainment in speech processing during working memory load

“…Eye blinks were classified as samples in the time series where the absolute value of the pupil diameter exceeded three standard deviations of the mean pupil diameter. Blink-corrupted segments were linearly interpolated from 350 ms before to 700 ms after the blink (Wendt et al, 2016). Trials containing more than 20% of corrupted data were rejected from further analysis.…”

“…This allowed us to examine the individual and combined effects of WM updating (n-back level) and inhibition (noise level) load during continuous speech processing. We recorded the EEG as well as changes in pupil sizes which are often used as a physiological marker of WM demands (Van Gerven et al, 2004;Zekveld et al, 2010;Scharinger et al, 2015;Wendt et al, 2016). To examine potential differences in speech entrainment during the different load conditions, we used regression techniques to analyse the relationship between ongoing low-frequency cortical activity and envelope fluctuations in the corresponding speech signal (Lalor et al, 2009;Ding & Simon, 2012).…”