Robust Endpoint detection in Mandarin Based on MFCC and Short-time Correlation Coefficient
Endpoint Detection is the process of cutting the signal into pieces according to its syllables or identifying the important part of a speech segment for further processing, which is a significant part in speech recognition. Recognition accuracy and robustness of the traditional methods for example, the short-time energy spectral and Zero-pass Ratio analysis will decrease sharply with the Signal-to-Noise-Ratio (SNR) going down. Base on some special feathers of Mandarin, a new robust algorithm with the combined using of MFCC and Shorttime Correlation Coefficient Analysis will be described in this paper, which has excellent noise immunity. The experimental results show that even with a lower SNR, the recognition accuracy is still higher and more stable than the other algorithm, and have great potential in speech signal processing.
Endpoint Detection Mandarin MFCC Correlation Coefficient Recognition accuracy noise immunity
Gang XU Bo Tong XiaoWei He
Department of Electrical and Electronic Engineering North China Electric Power University Beijing 10 National Development and Reform Commission National Academy of Material Reserve Beijing, China
国际会议
长沙
英文
1288-1291
2009-10-10（万方平台首次上网日期，不代表论文的发表时间）