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arXiv · 1911.06615

Deep learning methods in speaker recognition: a review

Dávid Sztahó·György Szaszák·András Beke
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Abstract

This paper summarizes the applied deep learning practices in the field of speaker recognition, both verification and identification. Speaker recognition has been a widely used field topic of speech technology. Many research works have been carried out and little progress has been achieved in the past 5-6 years. However, as deep learning techniques do advance in most machine learning fields, the former state-of-the-art methods are getting replaced by them in speaker recognition too. It seems that DL becomes the now state-of-the-art solution for both speaker verification and identification. The standard x-vectors, additional to i-vectors, are used as baseline in most of the novel works. The increasing amount of gathered data opens up the territory to DL, where they are the most effective.

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BibTeXRIS

Dávid Sztahó, György Szaszák, András Beke. 2019-11-14. Deep learning methods in speaker recognition: a review. https://doi.org/10.3311/ppee.17024

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