Neural Responses to Speech-Specific Modulations Derived from a Spectro-Temporal Filter Bank

This paper analyzes the application of methods developed in automatic speech recognition (ASR) to better understand neural activity measured with electrocorticography (ECoG) during the presentation of speech. ECoG data is collected from temporal cortex in two subjects listening to a matrix sentence test. We investigate the relation of ECoG signals and acoustic speech that has been processed with spectro-temporal filters, which have been shown to produce robust and reliable representations for speech applications. The organization of spectro-temporal filters into a filter bank allows for a straight-forward separation into spectral or temporal only, as well as true spectro-temporal components. We find electrodes positioned over the superior temporal gyrus that is associated with the auditory cortex to show significant specific high gamma activity to fine temporal and spectro-temporal patterns present in speech. This indicates that representations developed in machine listening are a suitable tool for the analysis of biosignals.