Non-stationary noise estimation method based on bias-residual component decomposition for robust speech recognition

Masakiyo Fujimoto*, Shinji Watanabe, Tomohiro Nakatani

*この研究の対応する著者

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

This paper addresses a noise suppression problem, namely the estimation of non-stationary noise sequences. In this problem, we assume that non-stationary noise can be decomposed into stationary and non-stationary components. These components are described respectively as the bias factor and the residual signal between the bias component and noise at each frame. This decomposition clarifies the role of each component, thus enabling us to apply a suitable parameter estimation technique to each component. In this paper, the bias component is estimated by the EM algorithm with the entire observed signal sequence. On the other hand, the residual component is sequentially estimated by multiplying the extended Kalman filter with the EM algorithm. In the evaluation results, we confirmed that the proposed method improved speech recognition accuracy compared with the noise estimation methods without component decomposition.

本文言語English
ホスト出版物のタイトル2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
ページ4816-4819
ページ数4
DOI
出版ステータスPublished - 2011 8月 18
外部発表はい
イベント36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
継続期間: 2011 5月 222011 5月 27

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

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
国/地域Czech Republic
CityPrague
Period11/5/2211/5/27

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

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