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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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.
収録刊行物
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- Acoustical Science and Technology
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Acoustical Science and Technology 26 (6), 511-522, 2005
一般社団法人 日本音響学会
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詳細情報 詳細情報について
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- CRID
- 1390282680067409664
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- NII論文ID
- 110003143602
- 120005716756
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- NII書誌ID
- AA11501808
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- ISSN
- 13475177
- 03694232
- 13463969
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- HANDLE
- 10061/7809
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- NDL書誌ID
- 7492957
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- IRDB
- NDL
- Crossref
- NDL-Digital
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可