Noise robustness in the auditory representation of speech signals

Authors:
Kuansan Wang;Shihab A. Shamma;William J. Byrne
Affiliations:
Institute of Systems Research and Department of Electrical Engineering, University of Maryland, College Park, MD;Institute of Systems Research and Department of Electrical Engineering, University of Maryland, College Park, MD;Institute of Systems Research and Department of Electrical Engineering, University of Maryland, College Park, MD
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Year:
1993

Citing 2
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The auditory processing and recognition of speech

HLT '89 Proceedings of the workshop on Speech and Natural Language
Auditory nerve representation as a front-end for speech recognition in a noisy environment

Computer Speech and Language

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Abstract

A common sequence of operations in the early stages of most biological sensory systems is a wavelet transform followed by a compressive nonlinearity. In this paper, we explore the contribution of these operations to the formation of robust and perceptually significant representations in the auditory system. It is demonstrated that the neural representation of a complex signal such as speech is derived from a highly reduced version of its wavelet transform, specifically, from the distribution of its locally averaged zero-crossing rates along the temporal and scale axes. It is shown analytically that such encoding of the wavelet transform results in mutual suppressive interactions across its different scale representations. Suppression in turn endows the representation with enhanced spectral peaks and superior robustness in noisy environments. Examples using natural speech vowels are presented to illustrate the results.