Title :
Voice activity detection using a periodicity measure
Author_Institution :
Ensigma Ltd., Chepstow, UK
Abstract :
The author describes a voice activity detector (VAD) that can operate reliably in SNRs down to 0 dB and detect most speech at -5 dB. The detector applies a least-squares periodicity estimator to the input signal, and triggers when a significant amount of periodicity is found. It does not aim to find the exact talkspurt boundaries and, consequently, is most suited to speech-logging applications where it is easy to include a small margin to allow for any missed speech. The author discusses the problem of false triggering on nonspeech periodic signals and shows bow robustness to these signals can be achieved with suitable preprocessing and postprocessing.<>
Keywords :
least squares approximations; signal detection; speech analysis and processing; false triggering; least-squares periodicity estimator; nonspeech periodic signals; periodicity measure; postprocessing; preprocessing; speech-logging applications; voice activity detector;
Journal_Title :
Communications, Speech and Vision, IEE Proceedings I