Online directional speech enhancement using geometrically constrained independent vector analysis

Li Li, Kazuhito Koishida, Shoji Makino

Research output: Contribution to journalConference articlepeer-review

5 Citations (Scopus)

Abstract

This paper proposes an online dual-microphone system for directional speech enhancement, which employs geometrically constrained independent vector analysis (IVA) based on the auxiliary function approach and vectorwise coordinate descent. Its offline version has recently been proposed and shown to outperform the conventional auxiliary function approach-based IVA (AuxIVA) thanks to the properly designed spatial constraints. We extend the offline algorithm to online by incorporating the autoregressive approximation of an auxiliary variable. Experimental evaluations revealed that the proposed online algorithm could work in real-time and achieved superior speech enhancement performance to online AuxIVA in both situations where a fixed target was interfered by a spatially stationary or dynamic interference.

Original languageEnglish
Pages (from-to)61-65
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2020-October
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020 - Shanghai, China
Duration: 2020 Oct 252020 Oct 29

Keywords

  • Geometric constraint
  • Independent vector analysis (IVA)
  • Multichannel speech enhancement
  • Online
  • Real-time

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modelling and Simulation

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