Weighted Frequency Smoothing for Enhanced Speaker Localization

Hanan Beit-On, Tom Shlomo, Boaz Rafaely

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The coherent signal subspace method may be used in order to apply subspace localization methods (e.g. MUSIC) to coherent sources. This method involves a focusing process followed by frequency smoothing, which is intended to decorrelate source signals from coherent sources. In practice, however, only moderate decorrelation is obtained, which may lead to performance degradation. Although decorrelation can be improved by widening the smoothing bandwidth, a wider bandwidth may increase focusing error and the smoothing bandwidth is limited by the bandwidth of the actual signal. In this paper, a weighted frequency smoothing that improves decorrelation for a given bandwidth is proposed. It is shown that better decorrelation is obtained by selecting the weights to be inversely proportional to the source signal power at the given frequency. However, since the power of the source is not known, it is estimated by the trace of the array spatial covariance matrix. An experimental study is presented that investigates the effect of the proposed weighting on DOA estimation of speech sources in a reverberant environment.

Original languageEnglish
Pages (from-to)2090-2099
Number of pages10
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume31
DOIs
StatePublished - 1 Jan 2023

Keywords

  • Speaker localization
  • coherent signal subspace
  • direct path dominance test
  • weighted frequency smoothing

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mathematics
  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics

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