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Speaker-independent isolated word recognition using word-based vector quantization and hidden Markov models

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2 Author(s)
Cheung, Y.S. ; University of Hong Kong, Hong Kong ; Leung, S.

In this paper, we investigate the possibility of using word-based vector quantization with hidden Markov models for speaker-independent isolated word recognition. Two word-based algorithms were proposed and studied. Experiments were carried out on Chinese (Cantonese) digits spoken by 110 speakers (55 males and 55 females) in two databases. An improvement of about 3% in recognition rate was obtained in one of the word-based algorithms. The results and implications are discussed.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '87.  (Volume:12 )

Date of Conference:

Apr 1987