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Detail publikačního výsledku
NOVOTNÝ, O.; PLCHOT, O.; GLEMBEK, O.; BURGET, L.; MATĚJKA, P.
Originální název
Discriminatively Re-trained i-Vector Extractor For Speaker Recognition
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
In this work we revisit discriminative training of the i-vector extractorcomponent in the standard speaker verification (SV) system. Themotivation of our research lies in the robustness and stability of thislarge generative model, which we want to preserve, and focus itspower towards any intended SV task. We show that after generativeinitialization of the i-vector extractor, we can further refine itwith discriminative training and obtain i-vectors that lead to betterperformance on various benchmarks representing different acousticdomains.
Anglický abstrakt
Klíčová slova
i-vectors, i-vector extractor, speaker recogni-tion, speaker verification, discriminative training
Klíčová slova v angličtině
Autoři
Rok RIV
2020
Vydáno
12.05.2019
Nakladatel
IEEE Signal Processing Society
Místo
Brighton
ISBN
978-1-5386-4658-8
Kniha
Proceedings of 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Strany od
6031
Strany do
6035
Strany počet
5
URL
https://ieeexplore.ieee.org/document/8682590
BibTex
@inproceedings{BUT160000, author="Ondřej {Novotný} and Oldřich {Plchot} and Ondřej {Glembek} and Lukáš {Burget} and Pavel {Matějka}", title="Discriminatively Re-trained i-Vector Extractor For Speaker Recognition", booktitle="Proceedings of 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)", year="2019", pages="6031--6035", publisher="IEEE Signal Processing Society", address="Brighton", doi="10.1109/ICASSP.2019.8682590", isbn="978-1-5386-4658-8", url="https://ieeexplore.ieee.org/document/8682590" }
Dokumenty
novotny_icassp2019_0006031