Deep Speaker Feature Learning for Text-Independent Speaker Verification

Abstract

Recently deep neural networks (DNNs) have been used to learn speaker features. However, the quality of the learned features is not sufficiently good, so a complex back-end model, either neural or probabilistic, has to be used to address the residual uncertainty when applied to speaker verification, just as with raw features. This paper presents a… (More)

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Cite this paper

@inproceedings{Li2017DeepSF, title={Deep Speaker Feature Learning for Text-Independent Speaker Verification}, author={Lantian Li and Yixiang Chen and Ying Shi and Zhiyuan Tang and Dong Wang}, booktitle={INTERSPEECH}, year={2017} }