Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (10): 147-150.

### Application of fuzzy entropy in speech endpoint detection in car environments

EN De, ZHANG Fenglei, ZHANG Zhao, HU Shengqiang

1. College of Electrical?Engineering and Automation, Henan Polytechnic University, Jiaozuo, Henan 454000, China
• Online:2016-05-15 Published:2016-05-16

### 模糊熵在车载环境下语音端点检测中的应用

1. 河南理工大学 电气工程与自动化学院，河南 焦作 454000

Abstract: In order to improve the accuracy of speech endpoint detection in car environment, introduces a new measure of time series complexity, fuzzy entropy, and applies it to the characterization of speech. With sample entropy and fuzzy entropy respectively to the characterization of speech signals in car environments, and uses fuzzy C-means clustering algorithm and Bayesian information criterion algorithm, estimates the thresholds of the characteristics, then by using dual threshold method for endpoint detection. Experimental results demonstrate that, the fuzzy entropy method can distinguish the noise and speech signals better and has better performance of endpoint detection than sample entropy in car environments, the accuracy rate of fuzzy entropy method is superior to sample entropy method more than 16% in the same environments.