Title :
Robust Voice Activity Detection at Noisy Environment Using Average Estimate Least Mean Square Filter
Author :
Sang-Yeob Oh ; Chan-Shik Ahn
Author_Institution :
Dept. of Interactive media, Gachon Univ., Seongnam, South Korea
Abstract :
In this paper, noise gets reduced with an average estimate LMS filter in a car noise environment so robust voice activities are being detected in a car noise environment. For the noise reduction, an average estimate LMS filter, which is a method for maintaining a source feature of speech and decreasing damages on speech information, is used in a speech signal detection process to reduce noise from a polluted speech signal. An average estimator was calculated and a step size of a LMS filter was controlled with a frame measure to improve an adaptation speed. Moreover, the starting point of result speech, comparing to the previous method of using frame energy was found to be improved by 1.7% and 3.7% of an error rate and an end point error rate, respectively.
Keywords :
acoustic signal detection; filtering theory; least mean squares methods; signal denoising; speech processing; LMS filter step size control; adaptation speed improvement; average estimate LMS filter; average estimate least mean square filter; car noise environment; end point error rate; frame measure; noise reduction; noisy environment; polluted speech signal; robust voice activity detection; speech information; speech signal detection process; speech source feature; Finite impulse response filters; Information filtering; Least squares approximations; Noise; Robustness; Speech; Speech processing;
Conference_Titel :
Information Science and Applications (ICISA), 2013 International Conference on
Conference_Location :
Suwon
Print_ISBN :
978-1-4799-0602-4
DOI :
10.1109/ICISA.2013.6579394