Publication

P300 indicates context-dependent change in speech quality beyond phonological change

Stefan Uhrig, Gabriel Mittag, Sebastian Möller, Jan-Niklas Voigt-Antons

In: Journal of Neural Engineering (JNE) 16 6 Pages 1-17 IOP Publishing 2019.

Abstract

Objective. Non-invasive physiological methods like electroencephalography (EEG) are increasingly employed to assess human information processing during exposure to multimedia signals. In the quality engineering field, previous research has promoted the utility of the P300 event-related brain potential (ERP) component for indicating variation in quality perception. The present study provides a starting point to test whether the P300 and its two subcomponents, P3a and P3b, are truly reflective of changes in the perceived quality of transmitted speech signals given the presence of other, quality-unrelated changes in acoustic stimulation. Approach. High-quality and degraded variants of spoken words were presented in a two-feature oddball task, which required participants to actively respond to rarely occurring ‘target’ stimuli within a series of frequent ‘standard’ stimuli, thereby eliciting ERP waveforms. Target presentations involved either single quality changes or concurrent double changes in quality and the initial phoneme. Main results. In case additional phonological change was present, only varying quality of standard stimuli caused significant modulations in P3a and P3b characteristics (N = 32). Thus, the formation of different short-term quality references exerted a persisting influence on the auditory processing of transmitted speech. Significance. The obtained results elucidate the importance of contextual and content-related influencing factors for proving the validity of the P300 as a psychophysiological indicator of speech quality change. Associated questions regarding the transfer of ERP-based quality assessment into more practically relevant measurement contexts are discussed.

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz