A robust estimation method of noise mixture model for noise suppression

Masakiyo Fujimoto*, Shinji Watanabe, Tomohiro Nakatani

*この研究の対応する著者

研究成果: Conference article査読

4 被引用数 (Scopus)

抄録

Vector Taylor series (VTS)-based noise suppression usually employs a single Gaussian distribution for the noise model. However, it is insufficient for non-stationary noise which has a multi-peak distribution. It is very complex to estimate multi-peak distribution of the noise, when we deal with the noise as random variables or hidden variables. To solve these problems, we investigate a way of estimating the noise mixture model by using a minimum mean squared error (MMSE) estimate of the noise. By iterating the MMSE estimation of noise and noise model estimation, the proposed method realizes the simultaneous optimization of both the observed signal model and the noise model. The proposed method significantly outperformed the VTS-based approach, and the maximum improvement in the word error rate was about 12%.

本文言語English
ページ(範囲)697-700
ページ数4
ジャーナルProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版ステータスPublished - 2011
外部発表はい
イベント12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
継続期間: 2011 8月 272011 8月 31

ASJC Scopus subject areas

  • 言語および言語学
  • 人間とコンピュータの相互作用
  • 信号処理
  • ソフトウェア
  • モデリングとシミュレーション

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