In this paper, a new auditory-based speech processing system based on the biologically rooted property of average localized synchrony detection (ALSD) is proposed. The system detects periodicity in the speech signal at Bark-scaled frequencies while reducing the response's spurious peaks and sensitivity to implementation mismatches, and hence presents a consistent and robust representation of the formants. The system is evaluated for its formant extraction ability while reducing spurious peaks. It is compared with other auditory-based front-end processing systems in the task of vowel recognition on clean speech from the TIMIT database and in the presence of noise. The results illustrate the advantage of the ALSD system in extracting the formants and reducing the spurious peaks. They also indicate the superiority of the synchrony measures over the mean-rate in the presence of noise.
Date of this Version
speech recognition, ALSD, average localized synchrony detection, Bark-scaled frequencies, auditory-based front-end processing systems, auditory-based speech processing, average localized synchrony detection, formants, mean-rate noise periodicity, speech signal, synchrony measures, vowel recognition
Date Posted: 20 October 2005
This document has been peer reviewed.