Noise variance estimation for kaiman filtering of noisy speech

Wooil Kim, Hanseok Ko

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)


This paper proposes an algorithm that adaptively estimates time-varying noise variance used in Kaiman filtering for real-time speech signal enhancement. In the speech signal contaminated by white noise, the spectral components except dominant ones in high frequency band are expected to reflect the noise energy. Our approach is first to find the dominant energy bands over speech spectrum using LPC. We then calculate the average value of the actual spectral components over the high frequency region excluding the dominant energy bands and use it as the noise variance. The resulting noise variance estimate is then applied to Kaiman filtering to suppress the background noise. Experimental results indicate that the proposed approach achieves a significant improvement in terms of speech enhancement over those of the conventional Kaiman filtering that uses the average noise power over silence interval only. As a refinement of our results, we employ multiple-Kalman filtering with multiple noise models and improve the intelligibility.

Original languageEnglish
Pages (from-to)155-160
Number of pages6
JournalIEICE Transactions on Information and Systems
Issue number1
Publication statusPublished - 2001


  • Dominant energy band
  • Enhancement
  • Kaiman filtering
  • Multiple kaiman filtering
  • Noise variance
  • Speech

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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