A comparison of auditory models for speaker independent phoneme recognition

Authors:
Timothy R. Anderson
Affiliations:
Armstrong Laboratory, Wright-Patterson AFB, OH
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Year:
1993

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Abstract

Neural networks that employ unsupervised learning were used on the output of two different models of the auditory periphery to perform phoneme recognition. Experiments which compared the performance of these two auditory model representations with that of Mel-Cepstral Coefficients show that the auditory models perform significantly better (t-test, p