Robust voice activity detection using cepstral features
- 30 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 139, 321-324
- https://doi.org/10.1109/tencon.1993.327987
Abstract
This paper reviews algorithms which rely on the analysis of time domain samples to provide energy and zero-crossing rates, together with more recent algorithms that use different methods for speech detection. We then examine a different approach using cepstral analysis, showing a high degree of amplitude and noise level independence. We show that a cepstral based algorithm exhibits a high degree of independence to levels of background noise and successful speech end-pointing can be achieved via thresholding cepstral distance measures. Through the use of a noise code-book we are able to provide a successful reference for Euclidean distance measures in the voice detection algorithm.Keywords
This publication has 6 references indexed in Scilit:
- The voice activity detector for the Pan-European digital cellular mobile telephone servicePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- A comparative study of cepstral lifters and distance measures for all pole models of speech in noisePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Voice activity detection using a periodicity measureIEE Proceedings I Communications, Speech and Vision, 1992
- A Study of On-Off Characteristics of Conversational SpeechIEEE Transactions on Communications, 1986
- Speech enhancement using a soft-decision noise suppression filterIEEE Transactions on Acoustics, Speech, and Signal Processing, 1980
- Algorithm for determining the endpoints of isolated utterancesThe Journal of the Acoustical Society of America, 1974