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

Ryouichi Nishimura, Futoshi Asano, Yoiti Suzuki, Toshio Sone

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1027-1033
Number of pages7
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE84-A
Issue number4
Publication statusPublished - 2001 Apr

Keywords

  • Kalman filter
  • Speech enhancement
  • Time-frequency pattern
  • Wavelet transform

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

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