Low Latency Online Source Separation and Noise Reduction Based on Joint Optimization with Dereverberation

Tetsuya Ueda*, Tomohiro Nakatani, Rintaro Ikeshita, Keisuke Kinoshita, Shoko Araki, Shoji Makino

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes low latency online source separation in noisy environments. An approach based on weighted prediction error dereverberation was recently proposed to solve the degradation caused by using low latency online source separation. Although this approach can also reduce noise by increasing the number of microphones and separating the noise as additional sources, the calculation cost prohibitively increases. To solve this problem, this paper incorporates techniques used in independent vector extraction (IVE) into the above conventional approach. Because IVE can skip most of the calculations for estimating noise by assuming that it is a stationary Gaussian, our proposed method achieves effective and computationally efficient noise reduction using many microphones. Experiments in a noisy car environment show that our proposed online method simultaneously separates sources and reduces noise with low latency (< 12 ms) processing.

Original languageEnglish
Title of host publication29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1000-1004
Number of pages5
ISBN (Electronic)9789082797060
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event29th European Signal Processing Conference, EUSIPCO 2021 - Dublin, Ireland
Duration: 2021 Aug 232021 Aug 27

Publication series

NameEuropean Signal Processing Conference
Volume2021-August
ISSN (Print)2219-5491

Conference

Conference29th European Signal Processing Conference, EUSIPCO 2021
Country/TerritoryIreland
CityDublin
Period21/8/2321/8/27

Keywords

  • Blind dereverberation
  • Blind source separation
  • Independent vector extraction
  • Low latency
  • Online

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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