TY - GEN
T1 - Using online model comparison in the variational bayes framework for online unsupervised voice activity detection
AU - Cournapeau, David
AU - Watanabe, Shinji
AU - Nakamura, Atsushi
AU - Kawahara, Tatsuya
PY - 2010
Y1 - 2010
N2 - This paper presents the use of online Variational Bayes method for online Voice Activity Detection (VAD) in an unsupervised context. In conventional VAD, the final step often relies on state machines whose parameters are heuristically tuned. The goal of this study is to propose a solid statistical scheme for VAD using online model comparison which is provided from the Variational Bayes framework. In this scheme, two models are estimated online in parallel: one for the noise-only situation , and the other for the noise-plus-signal situation The VAD decision is done automatically depending on the selected model. An experimental evaluation on the CENSREC-1-C database shows a significant improvement by the proposed method compared to conventional statistical VAD methods.
AB - This paper presents the use of online Variational Bayes method for online Voice Activity Detection (VAD) in an unsupervised context. In conventional VAD, the final step often relies on state machines whose parameters are heuristically tuned. The goal of this study is to propose a solid statistical scheme for VAD using online model comparison which is provided from the Variational Bayes framework. In this scheme, two models are estimated online in parallel: one for the noise-only situation , and the other for the noise-plus-signal situation The VAD decision is done automatically depending on the selected model. An experimental evaluation on the CENSREC-1-C database shows a significant improvement by the proposed method compared to conventional statistical VAD methods.
KW - Robustness
KW - Sequential estimation
KW - Variational bayes
KW - Voice activity detection
UR - http://www.scopus.com/inward/record.url?scp=78049371339&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78049371339&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2010.5495610
DO - 10.1109/ICASSP.2010.5495610
M3 - Conference contribution
AN - SCOPUS:78049371339
SN - 9781424442966
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 4462
EP - 4465
BT - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Y2 - 14 March 2010 through 19 March 2010
ER -