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Recent studies have shown that phase information contains speaker characteristics. A new extraction method to extract pitch synchronous phase information has been proposed and shown that it was very effective under channel matched condition. However, phase changes between different channels. Therefore, the speaker recognition performance is drastically(More)
Probabilistic linear discriminant analysis (PLDA) has shown to be an effective model for disentangling speaker and channel variability in the i-vector space for text-independent speaker verification. The speaker and channel subspaces in the PLDA model are typically trained by optimizing the maximum likelihood (ML) criterion. PLDA assumes that i-vectors are(More)
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