Speech Segregation Using an Auditory Vocoder With Event-Synchronous Enhancements

We propose a new method to segregate concurrent speech sounds using an auditory version of a channel vocoder. The auditory representation of sound, referred to as an "auditory image," preserves fine temporal information, unlike conventional window-based processing systems. This makes it possible to segregate speech sources with an event synchronous procedure. Fundamental frequency information is used to estimate the sequence of glottal pulse times for a target speaker, and to repress the glottal events of other speakers. The procedure leads to robust extraction of the target speech and effective segregation even when the signal-to-noise ratio is as low as 0 dB. Moreover, the segregation performance remains high when the speech contains jitter, or when the estimate of the fundamental frequency FO is inaccurate. This contrasts with conventional comb-filter methods where errors in FO estimation produce a marked reduction in performance. We compared the new method to a comb-filter method using a cross-correlation measure and perceptual recognition experiments. The results suggest that the new method has the potential to supplant comb-filter and harmonic-selection methods for speech enhancement