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

Tohru Shimizu*, Hirofumi Yamamoto, Hirokazu Masataki, Shoichi Matsunaga, Yoshinori Sagisaka

*この研究の対応する著者

研究成果: Conference article査読

41 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)145-148
ページ数4
ジャーナルICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
1
出版ステータスPublished - 1996 1 1
外部発表はい
イベントProceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA
継続期間: 1996 5 71996 5 10

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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