Discriminative autoencoders for speaker verification.

ICASSP, pp.5375-5379, (2017)

Cited by: 12|Views19
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Abstract:

This paper presents a learning and scoring framework based on neural networks for speaker verification. The framework employs an autoencoder as its primary structure while three factors are jointly considered in the objective function for speaker discrimination. The first one, relating to the sample reconstruction error, makes the structu...More

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