In hearing research, pupillometry is an established method of studying listening effort. The focus of this study was to evaluate several pupil measures extracted from the Task-Evoked Pupil Responses (TEPRs) in speech-in-noise test. A range of analysis approaches was applied to extract these pupil measures, namely (a) pupil peak dilation (PPD); (b) mean pupil dilation (MPD); (c) index of pupillary activity; (d) growth curve analysis (GCA); and (e) principal component analysis (PCA). The effect of signal-to-noise ratio (SNR; Data Set A: -20 dB, -10 dB, +5 dB SNR) and luminance (Data Set B: 0.1 cd/m2, 360 cd/m2) on the TEPRs were investigated. Data Sets A and B were recorded during a speech-in-noise test and included TEPRs from 33 and 27 normal-hearing native Dutch speakers, respectively. The main results were as follows: (a) A significant effect of SNR was revealed for all pupil measures extracted in the time domain (PPD, MPD, GCA, PCA); (b) Two time series analysis approaches (GCA, PCA) provided modeled temporal profiles of TEPRs (GCA); and time windows spanning subtasks performed in a speech-in-noise test (PCA); and (c) All pupil measures revealed a significant effect of luminance. In conclusion, multiple pupil measures showed similar effects of SNR, suggesting that effort may be reflected in multiple aspects of TEPR. Moreover, a direct analysis of the pupil time course seems to provide a more holistic view of TEPRs, yet further research is needed to understand and interpret its measures. Further research is also required to find pupil measures less sensitive to changes in luminance.
Keywords: cluster-based permutation test; index of pupillary activity; listening effort; principal component analysis; pupillometry.