Voice Activity Detection in Personal Audio Recordings Using Autocorrelogram Compensation

Lee, Keansub; Ellis, Daniel P. W.

This paper presents a novel method for identifying regions of speech in the kinds of energetic and highly-variable noise present in 'personal audio' collected by body-worn continuous recorders. Motivated by psychoacoustic evidence that pitch is crucial in the perception and organization of sound, we use a noise-robust pitch detection algorithm to locate speech-like regions. To avoid false alarms resulting from background noise with strong periodic components (such as air-conditioning), we add a new channel selection scheme to suppress frequency subbands where the autocorrelation is more stationary than encountered in voiced speech. Quantitative evaluation shows that these harmonic noises are effectively removed by this compensation technique in the domain of autocorrelogram, and that detection performance is significantly better than existing algorithms for detecting the presence of speech in real-world personal audio recordings.


Also Published In

INTERSPEECH 2006: ICSLP: Proceedings of the Ninth International Conference on Spoken Language Processing: September 17 - 21, 2006, Pittsburgh, Pennsylvania, USA

More About This Work

Academic Units
Electrical Engineering
Published Here
June 27, 2012