Speech Extraction in a Car Interior Using Frequency-Domain ICA with Rapid Filter Adaptations


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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/8132

Title:	Speech Extraction in a Car Interior Using Frequency-Domain ICA with Rapid Filter Adaptations
Authors:	Daisuke Saitoh Atsunobu Kaminuma Hiroshi Saruwatari Tsuyoki Nishikawa Akinobu Lee
Issue Date:	Sep-2005
Start page:	2301
End page:	2304
Abstract:	This paper describes two new algorithms for blind source separation (BSS) based on frequency-domain independent component analysis (FDICA). One is FDICA with pre-filtering by a speech sub-band passing filter to slow down the learning speed in low signal-to-noise ratio (SNR) sub-bands. The other is FDICA with sub-band selection learning to reduce the number of iterations for those sub-bands. The results of speech recognition experiments show that each method can improve word accuracy by as much as 7% and that the second method can increase the speed by approximately 60%.
Description:	INTERSPEECH2005: the 9th European Conference on Speech Communication and technology, September 4-8, 2005, Lisbon, Portugal.
URI:	http://hdl.handle.net/10061/8132
Rights:	Copyright 2005 ISCA
Text Version:	Publisher
Appears in Collections:	情報科学研究科 / Graduate School of Information Science

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