Improved modulation spectrum enhancement methods for robust speech recognition

详细信息	查看全文 | 推荐本文 |

• 作者：Jeih-weih Hung ; ^{jwhung@ncnu.edu.tw} ; Wen-hsiang Tu ^{aero3016@ms45.hinet.net} ; Chien-chou Lai
• 关键词：Speech recognition ; Noise-robust feature ; Modulation spectrum
• 刊名：Signal Processing
• 出版年：2012
• 期刊代码：162_01651684
• 类别：et
• 出版时间：November, 2012
• 卷：92
• 期：11
• 页码：2791-2814
• 文件大小：5998 K

摘要

In this paper, we present two novel algorithms to improve the noise robustness of features in speech recognition: modulation spectrum replacement (MSR) and modulation spectrum filtering (MSF). The magnitude spectra of feature streams are updated by referring to the information collected in the clean training set, and the resulting new feature streams are more noise-robust to achieve higher recognition accuracy. In experiments conducted on the Aurora-2 noisy digit database, we show that the proposed MSR achieves an average relative error reduction rate of nearly 57%compared to baseline processing, and MSF is specifically effective in enhancing the features preprocessed by conventional feature normalization methods to achieve even better recognition accuracy in noise-corrupted situations.