Exploiting known sound source signals to improve ICA-based robot audition in speech separation and recognition

Ryu Takeda, Kazuhiro Nakadai, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno

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

18 Citations (Scopus)

Abstract

This paper describes a new semi-blind source separation (semi-BSS) technique with independent component analysis (ICA) for enhancing a target source of interest and for suppressing other known interference sources. The semi-BSS technique is necessary for double-talk free robot audition systems in order to utilize known sound source signals such as self speech, music, or TV-sound, through a line-in or ubiquitous network. Unlike the conventional semi-BSS with ICA, we use the time-frequency domain convolution model to describe the reflection of the sound and a new mixing process of sounds for ICA. In other words, we consider that reflected sounds during some delay time are different from the original. ICA then separates the reflections as other interference sources. The model enables us to eliminate the frame size limitations of the frequency-domain ICA, and ICA can separate the known sources under a highly reverberative environment. Experimental results show that our method outperformed the conventional semi-BSS using ICA under simulated normal and highly reverberative environments.

Original languageEnglish
Title of host publicationProceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Pages1757-1762
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
Externally publishedYes
Event2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 - San Diego, CA, United States
Duration: 2007 Oct 292007 Nov 2

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Conference

Conference2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
CountryUnited States
CitySan Diego, CA
Period07/10/2907/11/2

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Takeda, R., Nakadai, K., Komatani, K., Ogata, T., & Okuno, H. G. (2007). Exploiting known sound source signals to improve ICA-based robot audition in speech separation and recognition. In Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 (pp. 1757-1762). [4399297] (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2007.4399297