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Phonetically sensitive discriminants for improved speech recognition

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1 Author(s)
Doddington, G.R. ; Texas Instrum. Inc., Dallas, TX, USA

A phonetically sensitive transformation of speech features has yielded significant improvement in speech-recognition performance. This (linear) transformation of the speech feature vector is designed to discriminate against out-of-class confusion data and is a function of phonetic state. Evaluation of the technique on the TI/NBS connected digit database demonstrates word (sentence) error rates of 0.5% (1.5%) for unknown-length strings and 0.2% (0.6%) for known-length strings. These error rates are two to three times lower than the best previously reported results and suggest that significant improvements in speech-recognition system performance can be achieved by better acoustic-phonetic modeling

Published in:

Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on

Date of Conference:

23-26 May 1989