Speech Categorization Reveals the Role of Early-Stage Temporal-Coherence Processing in Auditory Scene Analysis.

Temporal coherence of sound fluctuations across spectral channels is thought to aid auditory grouping and scene segregation. Although prior studies on the neural bases of temporal-coherence processing focused mostly on cortical contributions, neurophysiological evidence suggests that temporal-coherence-based scene analysis may start as early as the cochlear nucleus (i.e., the first auditory region supporting cross-channel processing over a wide frequency range). Accordingly, we hypothesized that aspects of temporal-coherence processing that could be realized in early auditory areas may shape speech understanding in noise. We then explored whether physiologically plausible computational models could account for results from a behavioral experiment that measured consonant categorization in different masking conditions. We tested whether within-channel masking of target-speech modulations predicted consonant confusions across the different conditions and whether predictions were improved by adding across-channel temporal-coherence processing mirroring the computations known to exist in the cochlear nucleus. Consonant confusions provide a rich characterization of error patterns in speech categorization, and are thus crucial for rigorously testing models of speech perception; however, to the best of our knowledge, they have not been used in prior studies of scene analysis. We find that within-channel modulation masking can reasonably account for category confusions, but that it fails when temporal fine structure cues are unavailable. However, the addition of across-channel temporal-coherence processing significantly improves confusion predictions across all tested conditions. Our results suggest that temporal-coherence processing strongly shapes speech understanding in noise and that physiological computations that exist early along the auditory pathway may contribute to this process.