End-to-End DNN Based Speaker Recognition Inspired by i-Vector and PLDA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU130738" target="_blank" >RIV/00216305:26230/18:PU130738 - isvavai.cz</a>
Result on the web
<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=11724" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=11724</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP.2018.8461958" target="_blank" >10.1109/ICASSP.2018.8461958</a>
Alternative languages
Result language
angličtina
Original language name
End-to-End DNN Based Speaker Recognition Inspired by i-Vector and PLDA
Original language description
Recently, several end-to-end speaker verification systems based on deep neural networks (DNNs) have been proposed. These systems have been proven to be competitive for text-dependent tasks as well as for text-independent tasks with short utterances. However, for text-independent tasks with longer utterances, end-to-end systems are still outperformed by standard i-vector + PLDA systems. In this work, we develop an end-to-end speaker verification system that is initialized to mimic an i-vector + PLDA baseline. The system is then further trained in an end-to-end manner but regularized so that it does not deviate too far from the initial system. In this way we mitigate overfitting which normally limits the performance of endto- end systems. The proposed system outperforms the i-vector + PLDA baseline on both long and short duration utterances.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of ICASSP
ISBN
978-1-5386-4658-8
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
4874-4878
Publisher name
IEEE Signal Processing Society
Place of publication
Calgary
Event location
Calgary
Event date
Apr 15, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000446384605009