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Target sound extraction utilizing similarity between signals as index for learning of linear filter
Author(s) -
Suyama Kenji,
Takahashi Kota
Publication year - 2006
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.20141
Subject(s) - similarity (geometry) , speech recognition , computer science , filter (signal processing) , microphone , signal (programming language) , correlation coefficient , channel (broadcasting) , microphone array , artificial intelligence , pattern recognition (psychology) , acoustics , computer vision , machine learning , physics , sound pressure , telecommunications , image (mathematics) , programming language
In this paper, we propose a novel learning method of two‐channel linear filter for a target sound extraction in a non‐stationary noisy environment using a two‐channel microphone array. The method is based on a correlation coefficient between received sounds of two microphones. The cue signal, which has a correlation with a variation of S/N of the received sounds, is generated using the correlation coefficient and is applied to the learning. By several computer simulation results, a superior performance of the proposed method even at the consonant section of the speech signal is presented in comparison with the previously proposed method. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(3): 45–52, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20141