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题名: Continuous speech recognition based on ICA and geometrical learning
作者: Feng H (Feng Hao);  Cao WM (Cao Wenming);  Wang SJ (Wang Shoujue)
出版日期: 2006
会议日期: AUG 18-21, 2005
摘要: We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.
会议名称: 4th International Conference on Machine Learning and Cybernetics
会议文集: ADVANCES IN MACHINE LEARNING AND CYBERNETICS丛书标题: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
专题: 中国科学院半导体研究所(2009年前)_会议论文

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推荐引用方式:
Feng, H (Feng, Hao); Cao, WM (Cao, Wenming); Wang, SJ (Wang, Shoujue) .Continuous speech recognition based on ICA and geometrical learning .见:SPRINGER-VERLAG BERLIN .ADVANCES IN MACHINE LEARNING AND CYBERNETICS丛书标题: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE ,HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY ,2006,3930: 974-983
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