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题名: Digits speech recognition based on geometrical learning
作者: Cao WM;  Pan XX;  Wang SJ;  Hu J
发表日期: 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 a 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 via the Hilbert transform. 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 method based on ICA and geometrical learning outperforms HMM in different number of train samples.
刊名: ADVANCED DATA MINING AND APPLICATIONS
专题: 中国科学院半导体研究所(2009年前)_期刊论文

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推荐引用方式:
Cao, WM; Pan, XX; Wang, SJ; Hu, J .Digits speech recognition based on geometrical learning ,ADVANCED DATA MINING AND APPLICATIONS,2005 ,PROCEEDINGS 3584(0):415-422
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