基于协方差描述子和黎曼流形的语音情感识别<sup>*</sup>

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Abstract An algorithm for speech emotion recognition is proposed based on covariance descriptor and Riemannian manifold. According to the extracted acoustic features, covariance matrices are computed as the emotion descriptors of sentences. With the consideration of high dimensional characteristic of the space constructed by non-singular covariance matrices, an affine invariance metric is adopted to make the space meet the requirement of Riemannian manifold. With differential geometry, the speech emotion recognition is performed on the manifold. The experimental results show a significant improvement in recognition accuracy, especially under noisy environments.

Key words： Speech Emotion Recognition Covariance Descriptor Riemannian Manifold Noisy Environment Support Vector Machine (SVM)

Received: 27 October 2008

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	Articles by authors
	LIU Jia
	CHEN Chun
	YE Cheng-Xi
	LI Na
	BU Jia-Jun

Cite this article:

LIU Jia,CHEN Chun,YE Cheng-Xi等. Speech Emotion Recognition Based on Covariance Descriptor and Riemannian Manifold[J]. , 2009, 22(5): 673-677.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2009/V22/I5/673

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