Speech production knowledge in automatic speech recognition

被引:130
|
作者
King, Simon
Frankel, Joe
Livescu, Karen
McDermott, Erik
Richmond, Korin
Wester, Mirjam
机构
[1] Univ Edinburgh, Ctr Speech Technol Res, Edinburgh EH8 9LW, Midlothian, Scotland
[2] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA
[3] NTT Corp, Commun Sci Labs, Kyoto 6190237, Japan
来源
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA | 2007年 / 121卷 / 02期
基金
英国工程与自然科学研究理事会;
关键词
D O I
10.1121/1.2404622
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Although much is known about. how speech is produced, and research into speech production has resulted in measured articulatory data, feature systems of different kinds, and numerous models, speech production knowledge is almost totally ignored in current mainstream approaches to automatic speech recognition. Representations of speech production allow simple explanations for many phenomena observed in speech which cannot be easily analyzed from either acoustic signal or phonetic transcription alone. In this article, a survey of a growing body of work in which such representations are used to improve automatic speech recognition is provided. (c) 2007 Acoustical Society of America.
引用
收藏
页码:723 / 742
页数:20
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