Title :
Voice activity detection based on augmented statistical noise suppression
Author :
Obuchi, Yasunari ; Takeda, Ryu ; Kanda, Natsuki
Author_Institution :
Central Res. Lab., Hitachi Ltd., Tokyo, Japan
Abstract :
A new voice activity detection (VAD) algorithm using augmented statistical noise suppression is introduced. Statistical noise suppression is an effective tool for speech processing under noisy conditions. It achieves the best VAD performance when the noise suppression is augmented in various ways. The speech distortion, which is usually a severe side effect of strong noise suppression, does not affect the VAD performance, and the correctly estimated signal power provides accurate detection of speech. The performance of the proposed algorithm is evaluated using CENSREC-1-C public database, and it is confirmed that the proposed algorithm outperforms other algorithms such as the switching Kalman filter-based VAD.
Keywords :
Kalman filters; interference suppression; speech processing; CENSREC-1-C public database; augmented statistical noise suppression; noisy conditions; speech detection; speech distortion; speech processing; switching Kalman filter-based VAD; voice activity detection; Accuracy; Estimation; Noise measurement; Signal to noise ratio; Speech; Speech recognition;
Conference_Titel :
Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific
Conference_Location :
Hollywood, CA
Print_ISBN :
978-1-4673-4863-8