Using online model comparison in the variational bayes framework for online unsupervised voice activity detection

David Cournapeau*, Shinji Watanabe, Atsushi Nakamura, Tatsuya Kawahara

*この研究の対応する著者

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
ページ4462-4465
ページ数4
DOI
出版ステータスPublished - 2010 11月 8
外部発表はい
イベント2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
継続期間: 2010 3月 142010 3月 19

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN(印刷版)1520-6149

Conference

Conference2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
国/地域United States
CityDallas, TX
Period10/3/1410/3/19

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

引用スタイル