Estimation of articulatory gesture patterns from speech acoustics

被引：0

作者：

Ghosh, Prasanta Kumar ^{[1
]}

Narayanan, Shrikanth ^{[1
]}

Divenyi, Pierre ^{[2
]}

Goldstein, Louis ^{[3
]}

Saltzman, Elliot ^{[4
]}

机构：

[1] Univ So Calif, Dept Elect Engn, Los Angeles, CA 90089 USA

[2] EBIRE, Martinez, CA 94553 USA

[3] Univ So Calif, Dept Linguist, Los Angeles, CA 90089 USA

[4] Haskins Labs Inc, New Haven, CT 06511 USA

来源：

INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5 | 2009年

关键词：

gestural patterns; acoustic to gesture inversion; VOCAL-TRACT; MOTOR THEORY; PERCEPTION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We investigated dynamic programming (DP) and state-model (SM) approaches for estimating gestural scores from speech acoustics. We performed a word-identification task using the gestural pattern vector sequences estimated by each am proach. For a set of 75 randomly chosen words, we obtained the best word-identification accuracy (66.67%) using the DP approach. This result implies that considerable support for lexical access during speech perception might be provided by such a method of recovering gestural information from acoustics.

引用

页码：2767 / +

页数：2

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