Yun-Xiao Geng

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Model complexity selection is important in the task of speaker identification. A Bayesian information criterion (BIC) based approach for model complexity selection is proposed in this paper. The speaker models are trained with the speech features. Then the BIC values of speaker models are calculated. In order to reduce the computation of training speaker(More)
Model compensation is an important means to improve the robustness of speaker recognition in noise environment. The robust speaker recognition approach based on model compensation is proposed in this paper. The proposed method combines data reliability estimation and feature components effectiveness estimation, so the errors of the second kind due to the(More)
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