Robust Joint Estimation of Multimicrophone Signal Model Parameters

Andreas I. Koutrouvelis, Richard C. Hendriks, Richard Heusdens, Jesper Jensen

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
72 Downloads (Pure)

Abstract

One of the biggest challenges in multimicrophone applications is the estimation of the parameters of the signal model, such as the power spectral densities (PSDs) of the sources, the early (relative) acoustic transfer functions of the sources with respect to the microphones, the PSD of late reverberation, and the PSDs of microphone-self noise. Typically, existing methods estimate subsets of the aforementioned parameters and assume some of the other parameters to be known a priori. This may result in inconsistencies and inaccurately estimated parameters and potential performance degradation in the applications using these estimated parameters. So far, there is no method to jointly estimate all the aforementioned parameters. In this paper, we propose a robust method for jointly estimating all the aforementioned parameters using confirmatory factor analysis. The estimation accuracy of the signal-model parameters thus obtained outperforms existing methods in most cases. We experimentally show significant performance gains in several multimicrophone applications over state-of-the-art methods.

Original languageEnglish
Article number8691792
Pages (from-to)1136-1150
Number of pages15
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume27
Issue number7
DOIs
Publication statusPublished - 2019

Bibliographical note

Accepted author manuscript

Keywords

  • Confirmatory factor analysis
  • dereverberation
  • joint diagonalization
  • multimicrophone
  • source separation
  • speech enhancement

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