Kernel multimodal discriminant analysis for speaker verification
In this paper, we propose a robust speaker feature extraction method using kernel multimodal Fisher discriminant analysis (kernel MFDA). Kernel MFDA has been designed to have the characteristics both of kernel principal component analysis (kernel PCA) and kernel Fisher discriminant analysis (kernel...
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Published in | 2010 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 4498 - 4501 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
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IEEE
01.03.2010
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Abstract | In this paper, we propose a robust speaker feature extraction method using kernel multimodal Fisher discriminant analysis (kernel MFDA). Kernel MFDA has been designed to have the characteristics both of kernel principal component analysis (kernel PCA) and kernel Fisher discriminant analysis (kernel FDA). Therefore, the feature vectors extracted by kernel MFDA are denoised as well as discriminated. For evaluation, we compare our proposed method with principal component analysis (PCA) and kernel PCA on the speaker verification systems. |
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AbstractList | In this paper, we propose a robust speaker feature extraction method using kernel multimodal Fisher discriminant analysis (kernel MFDA). Kernel MFDA has been designed to have the characteristics both of kernel principal component analysis (kernel PCA) and kernel Fisher discriminant analysis (kernel FDA). Therefore, the feature vectors extracted by kernel MFDA are denoised as well as discriminated. For evaluation, we compare our proposed method with principal component analysis (PCA) and kernel PCA on the speaker verification systems. |
Author | Il-Ho Yang Min-Seok Kim Ha-Jin Yu |
Author_xml | – sequence: 1 surname: Min-Seok Kim fullname: Min-Seok Kim email: ms@uos.ac.kr organization: Sch. of Comput. Sci., Univ. of Seoul, Seoul, South Korea – sequence: 2 surname: Il-Ho Yang fullname: Il-Ho Yang email: heisco@uos.ac.kr organization: Sch. of Comput. Sci., Univ. of Seoul, Seoul, South Korea – sequence: 3 surname: Ha-Jin Yu fullname: Ha-Jin Yu email: hjyu@uos.ac.kr organization: Sch. of Comput. Sci., Univ. of Seoul, Seoul, South Korea |
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Snippet | In this paper, we propose a robust speaker feature extraction method using kernel multimodal Fisher discriminant analysis (kernel MFDA). Kernel MFDA has been... |
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SubjectTerms | Computational complexity Covariance matrix Feature extraction Filtering Kernel Large-scale systems Principal component analysis Scattering Speaker recognition Speech enhancement Working environment noise |
Title | Kernel multimodal discriminant analysis for speaker verification |
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