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Speech recognition using dynamic transformation of phoneme templates depending on acoustic/phonetic environments

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2 Author(s)
Abe, Y. ; Mitsubishi Electr. Corp., Kamakura, Japan ; Nakajima, K.

A description is given of a phoneme-based speech recognition method using a linear model to represent the contextual variations in acoustic features caused by the phonemic context. A feature vector in a phonetic segment is decomposed into a context-independent vector, a context-dependent vector, and a residual vector. The context-independent vector is calculated by weighting a coefficient matrix to a context vector obtained from acoustic and/or phonetic data dynamically. Algebraic formulas for the maximum-likelihood estimations of the parameters in the model are derived by statistical modeling of the residual vector. For example, the proposed model achieved 97.9% word accuracy while the whole-word template model obtained 95.1% word accuracy

Published in:

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

Date of Conference:

23-26 May 1989

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