Missing-feature based speech recognition for two simultaneous speech signals separated by ICA with a pair of humanoid ears

Ryu Takeda, Shun'ichi Yamamoto, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno

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

11 Citations (Scopus)

Abstract

Robot audition is a critical technology in making robots symbiosis with people. Since we hear a mixture of sounds in our daily lives, sound source localization and separation, and recognition of separated sounds are three essential capabilities. Sound source localization has been recently studied well for robots, while the other capabilities still need extensive studies. This paper reports the robot audition system with a pair of omni-directional microphones embedded in a humanoid to recognize two simultaneous talkers. It first separates sound sources by Independent Component Analysis (ICA) with single-input multiple-output (SIMO) model. Then, spectral distortion for separated sounds is estimated to identify reliable and unreliable components of the spectrogram. This estimation generates the missing feature masks as spectrographic masks. These masks are then used to avoid influences caused by spectral distortion in automatic speech recognition based on missing-feature method. The novel ideas of our system reside in estimates of spectral distortion of temporal-frequency domain in terms of feature vectors. In addition, we point out that the voice-activity detection (VAD) is effective to overcome the weak point of ICA against the changing number of talkers. The resulting system outperformed the baseline robot audition system by 15 %.

Original languageEnglish
Title of host publication2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Pages878-885
Number of pages8
DOIs
Publication statusPublished - 2006 Dec 1
Externally publishedYes
Event2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 - Beijing, China
Duration: 2006 Oct 92006 Oct 15

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Conference

Conference2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
CountryChina
CityBeijing
Period06/10/906/10/15

Keywords

  • Automatic speech recognition
  • ICA
  • Missing-feature methods
  • Multiple speakers
  • Robot audition

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., Yamamoto, S., Komatani, K., Ogata, T., & Okuno, H. G. (2006). Missing-feature based speech recognition for two simultaneous speech signals separated by ICA with a pair of humanoid ears. In 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 (pp. 878-885). [4058472] (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2006.281741