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Abstract
Models of auditory processing, particularly of speech, face many difficulties. These difficulties include variability among speakers, variability in speech rate and robustness to moderate distortions such as time compression. In contrast to the ‘invariance of percept’ (across different speakers, of different sexes, using different intonation, and so on) is the observation that we are sensitive to the identity, sex and intonation of the speaker.
In previous work we have reported that a model based on ensembles of spectro-temporal feature detectors, derived from onset sensitive pre-processing of a limited class of stimuli, preserves significant information about the stimulus class. We have also shown that this is robust with respect to the exact choice of feature set, moderate time compression in the stimulus and speaker variation. Here we extend these results to show a) that by using a classifier based on a network of spiking neurons with spike-driven plasticity, the output of the ensemble constitutes an effective rate coding representation of complex sounds; and b) that the same set of spectro-temporal features concurrently preserve information about a range of qualitatively different classes into which the stimulus might fall. We show that it is possible for multiple views of the same pattern of responses to generate different percepts. This is consistent with suggestions that multiple parallel processes exist within the auditory ‘what’ pathway with attentional modulation enhancing the task-relevant classification type. We also show that the responses of the ensemble are sparse in the sense that a small number of features respond for each stimulus type. This has implications for the ensembles' ability to generalise, and to respond differentially to a wide variety of stimulus classes.