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Content Provider | IEEE Xplore Digital Library |
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Author | Nakajima, H. Nakadai, K. Hasegawa, Y. Tsujino, H. |
Copyright Year | 2008 |
Description | Author affiliation: Honda Res. Inst. Japan Co. Ltd., Saitama (Nakajima, H.; Nakadai, K.; Hasegawa, Y.; Tsujino, H.) |
Abstract | This paper describes a method to adaptively control a step-size parameter which is used for updating a separation matrix to extract a target sound source accurately in blind source separation (BSS). The design of the step-size parameter is essential when we apply BSS to real-world applications such as robot audition systems, because the surrounding environment dynamically changes in the real world. It is common to use a fixed step-size parameter that is obtained empirically. However, due to environmental changes and noises, the performance of BSS with the fixed step-size parameter deteriorates and the separation matrix sometimes diverges. We propose a general method that allows adaptive step-size control. The proposed method is an extension of Newton's method utilizing a complex gradient theory and is applicable to any BSS algorithm. Actually, we applied it to six types of BSS algorithms for an 8ch microphone array embedded in Honda ASIMO. Experimental results show that the proposed method improves the performance of these six BSS algorithms through experiments of separation and recognition for two simultaneous speeches. |
Starting Page | 149 |
Ending Page | 152 |
File Size | 254518 |
Page Count | 4 |
File Format | |
ISBN | 9781424414833 |
ISSN | 15206149 |
DOI | 10.1109/ICASSP.2008.4517568 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-03-31 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Programmable control Adaptive control Blind source separation Source separation Microphone arrays Robots Acoustic noise Working environment noise Newton method Speech Newton’s method robot audition blind source separation adaptive step-size |
Content Type | Text |
Resource Type | Article |
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