Effect of Central Limit Theorem non-compliance on blind separation of speech by negentropy maximization

Acoustical Science and Technology

Rajkishore Prasad¹  Kiyohiro Shikano¹  Hiroshi Saruwatari¹ 

[1] Graduate School of Information Science, Nara Institute of Science and Technology

关键词: Blind signal separation;    Independent component analysis;    Negentropy;    Central limit theorem;    Speech signal;    Microphone array;   

DOI  :  10.1250/ast.26.511

学科分类：声学和超声波

来源: Acoustical Society of Japan

【 摘 要 】

References(25)In this paper the blind separation of speech signals from their convoluted mixtures using frequency domain fixed-point independent component analysis algorithm, based on negentropy maximization, is presented. We also discuss fundamental problems of fixed-point ICA by negentropy maximization arising in the separation of the speech signal due to disobedience of the Central Limit Theorem (CLT) by the mixed speech data in the frequency domain. The experimental evidences show that CLT failure is happening due to the spectral sparseness of sources. We also present a blind method to mitigate the negative effects of this by combining null beamforming with the ICA. This combination gives a good result under the low reverberation conditions.

【 授权许可】

Unknown