Noise Adaptive Multi-stream Hybrid Sub-band Approach for Robust Speech Recognition

Zhang Jun; Wei Gang

Volume 28 Issue 7

Jan. 2011

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2006 > 28(7): 1183-1187

Zhang Jun, Wei Gang. Noise Adaptive Multi-stream Hybrid Sub-band Approach for Robust Speech Recognition[J]. Journal of Electronics & Information Technology, 2006, 28(7): 1183-1187.

Citation:

Zhang Jun, Wei Gang. Noise Adaptive Multi-stream Hybrid Sub-band Approach for Robust Speech Recognition[J]. Journal of Electronics & Information Technology, 2006, 28(7): 1183-1187.

Zhang Jun, Wei Gang. Noise Adaptive Multi-stream Hybrid Sub-band Approach for Robust Speech Recognition[J]. Journal of Electronics & Information Technology, 2006, 28(7): 1183-1187.

Citation:

Zhang Jun, Wei Gang. Noise Adaptive Multi-stream Hybrid Sub-band Approach for Robust Speech Recognition[J]. Journal of Electronics & Information Technology, 2006, 28(7): 1183-1187.

PDF( 235 KB)

Noise Adaptive Multi-stream Hybrid Sub-band Approach for Robust Speech Recognition

Zhang Jun,
Wei Gang

Received Date: 2004-11-05
Rev Recd Date: 2005-07-22
Publish Date: 2006-07-19

Abstract

Abstract

This paper first proposes a new method for evaluating the reliability of cepstral components and extends the marginalisation technique to cepstral recognizers. Then a noise adaptive multi-stream hybrid sub-band approach is proposed for robust speech recognition by making use of the complemental performances between full-band and sub-band cepstral marginalisation recognizers in different noises. Experimental results show that the proposed approach can turn to the less distorted data stream automatically and improve the robustness of the speech recognizer in various noisy environments effectively.

FullText(HTML)

References(1)

References

Mendel J M. White-noise estimators for seismic data processing in oil exploration[J]. IEEE Trans. Automatic Control, 1977, 22(5): 694706. .[2]Mendel J M. Optimal Seismic Deconvolution：an Estimation- based Approach[M]. New York：Academic Press，1983: 1.103.[3]Sun Shuli. Multi-sensor information fusion white noise filter weighted by scalars based on Kalman predictor[J].Automatica.2004, 40 (8):1447-[4]Sun Shuli，Deng Zili. Multi-sensor optimal information fusion Kalman filter[J]. Automatica, 2004, 40(6): 10171023. .[5]邓自立，高媛，李云等. 基于Kalman滤波的信息融合白噪声最优反卷积滤波器[J]. 科学技术与工程，2004，4(3)：169.171.[6]邓自立. 卡尔曼滤波与维纳滤波现代时间序列分析方法[M]. 哈尔滨：哈尔滨工业大学出版社，2000: 1.396.[7]邓自立. 自校正滤波理论及其应用现代时间序列分析方法[M]. 哈尔滨：哈尔滨工业大学出版社，2003: 1.343.

Relative Articles

Supplements(0)

Cited By

Proportional views