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In this paper, we propose a feature transformation method to maximize the distances between the Gaussian mixture models for speaker verification. The feature transformation matrix is optimized by using particle swarm optimization. We evaluate the transformation using YOHO speech data, and the transformation is applied to some speakers who give poor performance. As the result, the overall equal error...
In this paper, we propose a new feature transformation method that is optimized for diagonal covariance Gaussian mixture models which is used for a speaker identification system. We first define an object function as the distances between the Gaussian mixture components and rotate each plane in the feature space to maximize the object function. The optimal degrees of the rotations are found using...
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