LARGE VOCABULARY WORD RECOGNITION SYSTEM USING RULE-BASED NETWORK REPRESENTATION OF ACOUSTIC CHARACTERISTIC VARIATIONS.

Satoru Hayamizu, Kazuyo Tanaka, Kozo Ohta

研究成果: Conference article査読

4 被引用数 (Scopus)

抄録

A method to represent, acquire and implement acoustic-phonetic knowledge for large vocabulary word recognition is described. The knowledge is represented using networks of acoustic-phonetic segments, acquired from a speech database and stored as rules which are used to generate those networks. Different standard patterns of segments are used for each VCV or CVC environment. Network matching and segment clustering are used to implement an efficient recognition procedure. Experiments on speaker-independent isolated-word recognition were conducted with 10 male speakers' utterances. The word recognition accuracy was 99. 4% for 53 city names and 96. 0% for 492 words of the phonetically balanced word set, respectively.

本文言語English
ページ(範囲)211-214
ページ数4
ジャーナルICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
出版ステータスPublished - 1988
外部発表はい

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

フィンガープリント

「LARGE VOCABULARY WORD RECOGNITION SYSTEM USING RULE-BASED NETWORK REPRESENTATION OF ACOUSTIC CHARACTERISTIC VARIATIONS.」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル