A speech enhancement technique using Kalman filter with state vector of time-frequency patterns

Ryouichi Nishimura, Futoshi Asano, Yoiti Suzuki, Toshio Sone

研究成果: Article査読

1 被引用数 (Scopus)

抄録

A new speech enhancement technique is proposed assuming that a speech signal is represented in terms of a linear probabilistic process and that a noise signal is represented in terms of a stationary random process. Since the target signal, i.e., speech, cannot be represented by a stationary random process, a Wiener filter does not yield an optimum solution to this problem regarding the minimum mean variance. Instead, a Kalman filter may provide a suitable solution in this case. In the Kalman filter, a signal is represented as a sequence of varying state vectors, and the transition is dominated by transition matrices. Our proposal is to construct the state vectors as well as the transition matrices based on time-frequency pattern of signals calculated by a wavelet transformation (WT). Computer simulations verify that the proposed technique has a high potential to suppress noise signals.

本文言語English
ページ(範囲)1027-1033
ページ数7
ジャーナルIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
E84-A
4
出版ステータスPublished - 2001 4

ASJC Scopus subject areas

  • 信号処理
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • 電子工学および電気工学
  • 応用数学

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