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arXiv · 1904.01269

Experiments on Open-Set Speaker Identification with Discriminatively Trained Neural Networks

Stefano Imoscopi·Volodya Grancharov·Sigurdur Sverrisson·Erlendur Karlsson·Harald Pobloth
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Abstract

This paper presents a study on discriminative artificial neural network classifiers in the context of open-set speaker identification. Both 2-class and multi-class architectures are tested against the conventional Gaussian mixture model based classifier on enrolled speaker sets of different sizes. The performance evaluation shows that the multi-class neural network system has superior performance for large population sizes.

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Stefano Imoscopi, Volodya Grancharov, Sigurdur Sverrisson, Erlendur Karlsson, Harald Pobloth. 2019-04-02. Experiments on Open-Set Speaker Identification with Discriminatively Trained Neural Networks. https://arxiv.org/abs/1904.01269

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