Deep learning methods in speaker recognition: a review
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 pas...
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| creator | Sztahó, Dávid Szaszák, György Beke, András |
| description | 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. |
| doi_str_mv | 10.48550/arxiv.1911.06615 |
| format | Article |
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| subjects | Computer Science - Learning Computer Science - Sound Deep learning Machine learning Speech recognition Statistics - Machine Learning Verification |
| title | Deep learning methods in speaker recognition: a review |
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