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Spontaneous dialogue speech recognition using cross-word context constrained word graphs

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5 Author(s)
Shimizu, T. ; ATR Interpreting Telephony Res. Labs., Kyoto, Japan ; Yamamoto, H. ; Masataki, H. ; Matsunaga, S.
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This paper proposes a large vocabulary spontaneous dialogue speech recognizer using cross-word context constrained word graphs. In this method, two approximation methods “cross-word context approximation” and “lenient language score smearing” are introduced to reduce the computational cost for word graph generation. The experimental results using a “travel arrangement corpus” show that this recognition method achieves a word hypotheses reduction of 25-40% and a cpu-time reduction of 30-60% compared to without approximation, and that the use of class bigram scores as the expected language score for each lexicon tree node decreases the word error rate 25-30% compared to without approximation

Published in:

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on  (Volume:1 )

Date of Conference:

7-10 May 1996