Effect of Central Limit Theorem non-compliance on blind separation of speech by negentropy maximization
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- Prasad Rajkishore
- Graduate School of Information Science, Nara Institute of Science and Technology
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- Saruwatari Hiroshi
- Graduate School of Information Science, Nara Institute of Science and Technology
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- Shikano Kiyohiro
- Graduate School of Information Science, Nara Institute of Science and Technology
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Abstract
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.
Journal
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- Acoustical Science and Technology
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Acoustical Science and Technology 26 (6), 511-522, 2005
ACOUSTICAL SOCIETY OF JAPAN
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Keywords
Details 詳細情報について
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- CRID
- 1390282680067409664
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- NII Article ID
- 110003143602
- 120005716756
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- NII Book ID
- AA11501808
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- ISSN
- 13475177
- 03694232
- 13463969
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- HANDLE
- 10061/7809
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- NDL BIB ID
- 7492957
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- Text Lang
- en
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- Data Source
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- JaLC
- IRDB
- NDL
- Crossref
- NDL-Digital
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed