Mixed environment compensation based on maximum a posteriori estimation for robust speech recognition

被引：0
|
作者：
Haifeng Shen
Gang Liu
Jun Guo
机构：
[1] Beijing University of Posts and Telecommunications,
来源：
Artificial Intelligence Review | 2009年 / 32卷
关键词：
Robust speech recognition; Mixed environment compensation; MAP; EM;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Noise robustness is a fundamental problem for speech recognition system in the real environments. The paper presents mixed environment compensation technique in which feature compensation algorithm and acoustic model compensation algorithm is combined together. The target is to obtain the fine compensated static acoustic model and the dynamic compensated speech. Therefore, the modified speech sequence can well match the modified acoustic model. The experimental results show that significant performance improvement has been observed.
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页码：1 / 11
页数：10
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