Detail publikačního výsledku
Spoken Pass-Phrase Verification in the i-vector Space
ZEINALI, H.; BURGET, L.; SAMETI, H.; ČERNOCKÝ, J.
Originální název
Spoken Pass-Phrase Verification in the i-vector Space
Anglický název
Spoken Pass-Phrase Verification in the i-vector Space
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
The task of spoken pass-phrase verification is to decide whethera test utterance contains the same phrase as given enrollmentutterances. Beside other applications, pass-phrase verificationcan complement an independent speaker verification subsystemin text-dependent speaker verification. It can also be used forliveness detection by verifying that the user is able to correctlyrespond to a randomly prompted phrase. In this paper, we buildon our previous work on i-vector based text-dependent speakerverification, where we have shown that i-vectors extracted usingphrase specific Hidden Markov Models (HMMs) or using DeepNeural Network (DNN) based bottle-neck (BN) features help toreject utterances with wrong pass-phrases. We apply the samei-vector extraction techniques to the stand-alone task of speakerindependentspoken pass-phrase classification and verification.The experiments on RSR2015 and RedDots databases show thatvery simple scoring techniques (e.g. cosine distance scoring)applied to such i-vectors can provide results superior to thosepreviously published on the same data.
Anglický abstrakt
The task of spoken pass-phrase verification is to decide whethera test utterance contains the same phrase as given enrollmentutterances. Beside other applications, pass-phrase verificationcan complement an independent speaker verification subsystemin text-dependent speaker verification. It can also be used forliveness detection by verifying that the user is able to correctlyrespond to a randomly prompted phrase. In this paper, we buildon our previous work on i-vector based text-dependent speakerverification, where we have shown that i-vectors extracted usingphrase specific Hidden Markov Models (HMMs) or using DeepNeural Network (DNN) based bottle-neck (BN) features help toreject utterances with wrong pass-phrases. We apply the samei-vector extraction techniques to the stand-alone task of speakerindependentspoken pass-phrase classification and verification.The experiments on RSR2015 and RedDots databases show thatvery simple scoring techniques (e.g. cosine distance scoring)applied to such i-vectors can provide results superior to thosepreviously published on the same data.
Klíčová slova
spoken pass-phrase verification, i-vector, speaker verification
Klíčová slova v angličtině
spoken pass-phrase verification, i-vector, speaker verification
Autoři
ZEINALI, H.; BURGET, L.; SAMETI, H.; ČERNOCKÝ, J.
Rok RIV
2019
Vydáno
26.06.2018
Nakladatel
International Speech Communication Association
Místo
Les Sables d´Olonne
Kniha
Proceedings of Odyssey 2018
ISSN
2312-2846
Periodikum
Proceedings of Odyssey: The Speaker and Language Recognition Workshop Odyssey 2014, Joensuu, Finland
Svazek
2018
Číslo
6
Stát
Finská republika
Strany od
372
Strany do
377
Strany počet
6
URL
BibTex
@inproceedings{BUT155079,
author="Hossein {Zeinali} and Lukáš {Burget} and Hossein {Sameti} and Jan {Černocký}",
title="Spoken Pass-Phrase Verification in the i-vector Space",
booktitle="Proceedings of Odyssey 2018",
year="2018",
journal="Proceedings of Odyssey: The Speaker and Language Recognition Workshop Odyssey 2014, Joensuu, Finland",
volume="2018",
number="6",
pages="372--377",
publisher="International Speech Communication Association",
address="Les Sables d´Olonne",
doi="10.21437/Odyssey.2018-52",
issn="2312-2846",
url="https://www.fit.vut.cz/research/publication/11791/"
}Dokumenty