Abstract
In order to enhance the recognition performance of the i-vector speaker recognition system under unpredicted noise environment, an improved local preserve projection which was used for reduce dimension to i-vector is proposed on this paper. First, the nonzero eigenvalue is rejected when we solve the optimized objective function, only using the eigenvalue the value of which is greater than zero. A mapping matrix is obtained by solving a generalized eigenvalue problem which can settle the singular value problem which occurred in the traditional local preserve projection algorithm. The experiment result shows that the recognition performance of the method proposed in this paper is improved under several kinds of noise environments.
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Acknowledgments
This work was supported in part by the National Science-technology Support Plan Project of China under contract 1214ZGA008, the Nature Science Foundation of China under contract 61263031, and the Science Foundation of Gansu Province of China under contract 1010RJZA046.
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Wu, D. (2015). Speaker Recognition Based on i-Vector and Improved Local Preserving Projection. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46469-4_12
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DOI: https://doi.org/10.1007/978-3-662-46469-4_12
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