Unsupervised pronunciation grammar generation for non-native speech recognition

被引：0
|
作者：
Huang, Chien-Lin [1 ]
Wu, Chung-Hsien [1 ]
Chen, Yi [1 ]
Hsu, Chin-Shun [2 ]
Lee, Kuei-Ming [2 ]
机构：
[1] Natl Cheng Kung Univ, Dept Comp Sci & Informat Engn, Tainan 70101, Taiwan
[2] Inst Informat Ind, Tainan, Taiwan
来源：
TENCON 2007 - 2007 IEEE REGION 10 CONFERENCE, VOLS 1-3 | 2007年
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This study presents a novel approach to unsupervised pronunciation grammar generation for non-native speech recognition. Unsupervised pronunciation grammar generation includes pronunciation variation graph construction, stochastic Markov search and grammar selection. Context-dependent relation and phone broad class information are used for variation graph construction. Confidence measure and co-occurrence frequency are used to select the variants of pronunciation grammar for non-native speech modeling. Experiments show that unsupervised pronunciation grammar generation is suitable for the improvement of non-native speech recognition.
引用
收藏
页码：452 / +
页数：2
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