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Detail publikačního výsledku
NOVOTNÝ, O.; PLCHOT, O.; GLEMBEK, O.; BURGET, L.
Originální název
Factorization of Discriminatively Trained i-Vector Extractor for Speaker Recognition
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
In this work, we continue in our research on i-vector extractorfor speaker verification (SV) and we optimize its architecturefor fast and effective discriminative training. We were motivatedby computational and memory requirements caused bythe large number of parameters of the original generative ivectormodel. Our aim is to preserve the power of the originalgenerative model, and at the same time focus the model towardsextraction of speaker-related information. We show that it ispossible to represent a standard generative i-vector extractor bya model with significantly less parameters and obtain similarperformance on SV tasks. We can further refine this compactmodel by discriminative training and obtain i-vectors that leadto better performance on various SV benchmarks representingdifferent acoustic domains.
Anglický abstrakt
Klíčová slova
SRE
Klíčová slova v angličtině
Autoři
Rok RIV
2020
Vydáno
15.09.2019
Nakladatel
International Speech Communication Association
Místo
Graz
Kniha
Proceedings of Interspeech
ISSN
1990-9772
Periodikum
Svazek
2019
Číslo
9
Stát
Francouzská republika
Strany od
4330
Strany do
4334
Strany počet
5
URL
https://www.isca-speech.org/archive/Interspeech_2019/pdfs/1757.pdf
BibTex
@inproceedings{BUT159998, author="Ondřej {Novotný} and Oldřich {Plchot} and Ondřej {Glembek} and Lukáš {Burget}", title="Factorization of Discriminatively Trained i-Vector Extractor for Speaker Recognition", booktitle="Proceedings of Interspeech", year="2019", journal="Proceedings of Interspeech", volume="2019", number="9", pages="4330--4334", publisher="International Speech Communication Association", address="Graz", doi="10.21437/Interspeech.2019-1757", issn="1990-9772", url="https://www.isca-speech.org/archive/Interspeech_2019/pdfs/1757.pdf" }
Dokumenty
novotny_is2019_191757