Noise spectrum estimation with entropy-based VAD in non-stationary environments

Bing-Fei Wu*, Kun Ching Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

This study presents a fast adaptive algorithm for noise estimation in non-stationary environments. To make noise estimation adapt quickly to non-stationary noise environments, a robust entropy-based voice activity detection (VAD) is thus required. It is well-known that the entropy-based measure defined in spectral domain is very insensitive to the changing level of nose. To exploit the specific nature of straight lines existing on speech-only spectrogram, the proposed spectrum entropy measurement improved from spectrum entropy proposed by Shen et al. is further presented and is named band-splitting spectrum entropy (BSE). Consequently, the proposed recursive noise estimator including BSE-based VAD can update noise power spectrum accurately even if the noise-level quickly changes.

Original languageEnglish
Pages (from-to)479-485
Number of pages7
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE89-A
Issue number2
DOIs
StatePublished - 1 Jan 2006

Keywords

  • Noise measurement
  • Spectrum entropy
  • Voice activity detection

Fingerprint Dive into the research topics of 'Noise spectrum estimation with entropy-based VAD in non-stationary environments'. Together they form a unique fingerprint.

Cite this