Location of Repository

No, ….

By Ryu Takeda, Kazuhiro Nakadai, Toru Takahashi, Kazunori Komatani, Tetsuya Ogata, Hiroshi G. Okuno and Only Has

Abstract

Abstract — This paper presents the upper-limit evaluation of robot audition based on ICA-BSS in multi-source, barge-in and highly reverberant conditions. The goal is that the robot can automatically distinguish a target speech from its own speech and other sound sources in a reverberant environment. We focus on the multi-channel semi-blind ICA (MCSB-ICA), which is one of the sound source separation methods with a microphone array, to achieve such an audition system because it can separate sound source signals including reverberations with few assumptions on environments. The evaluation of MCSB-ICA has been limited to robot’s speech separation and reverberation separation. In this paper, we evaluate MCSB-ICA extensively by applying it to multi-source separation problems under common reverberant environments. Experimental results prove that MCSB-ICA outperforms conventional ICA by 30 points in automatic speech recognition performance

Topics: Speech Recognition
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.184.6647
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://winnie.kuis.kyoto-u.ac.... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.