Linearized distortion model for robust speech recognition in noisy environments

被引：0
|
作者：
He, Yong-Jun [1 ,2 ]
Han, Ji-Qing [1 ]
机构：
[1] School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
[2] School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
来源：
Tongxin Xuebao/Journal on Communications | 2010年 / 31卷 / 09期
关键词：
Linearization - Piecewise linear techniques;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The robustness of speech recognition system in noisy environments was investigated. The distortion model in Mel-frequency cepstral coefficient (MFCC) domain is highly non-linear and difficult to deal with. A new linear distortion model was proposed by replacing the logarithm operation with its piecewise linear interpolation function. Then the estimation of noise parameters and compensation of acoustic models were provided. The proposed method can avoid model error introduced by utilizing linearization methods based on vector Taylor series (VTS) expansion, and significantly improve the robustness of recognizer in noisy environments.
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页码：8 / 14
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