Utilizing VOiCES dataset for multichannel speaker verification with beamforming

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU136531" target="_blank" >RIV/00216305:26230/20:PU136531 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.isca-speech.org/archive/Odyssey_2020/abstracts/80.html" target="_blank" >https://www.isca-speech.org/archive/Odyssey_2020/abstracts/80.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21437/Odyssey.2020-27" target="_blank" >10.21437/Odyssey.2020-27</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Utilizing VOiCES dataset for multichannel speaker verification with beamforming

Popis výsledku v původním jazyce

VOiCES from a Distance Challenge 2019 aimed at the evaluation of speaker verification (SV) systems using single-channel trials based on the Voices Obscured in Complex Environmental Settings (VOiCES) corpus. Since it comprises recordings of the same utterances captured simultaneously by multiple microphones in the same environments, it is also suitable for multichannel experiments. In this work, we design a multichannel dataset as well as development and evaluation trials for SV inspired by the VOiCES challenge. Alternatives discarding harmful microphones are presented as well. We asses the utilization of the created dataset for x-vector based SV with beamforming as a front end. Standard fixed beamforming and NN-supported beamforming using simulated data and ideal binary masks (IBM) are compared with another variant of NNsupported beamforming that is trained solely on the VOiCES data. Lack of data revealed by experiments with VOiCESdata trained beamformer was tackled by means of a variant of SpecAugment applied to magnitude spectra. This approach led to as much as 10% relative improvement in EER pushing results closer to those obtained by a good beamformer based on IBMs.

Název v anglickém jazyce

Utilizing VOiCES dataset for multichannel speaker verification with beamforming

Popis výsledku anglicky

VOiCES from a Distance Challenge 2019 aimed at the evaluation of speaker verification (SV) systems using single-channel trials based on the Voices Obscured in Complex Environmental Settings (VOiCES) corpus. Since it comprises recordings of the same utterances captured simultaneously by multiple microphones in the same environments, it is also suitable for multichannel experiments. In this work, we design a multichannel dataset as well as development and evaluation trials for SV inspired by the VOiCES challenge. Alternatives discarding harmful microphones are presented as well. We asses the utilization of the created dataset for x-vector based SV with beamforming as a front end. Standard fixed beamforming and NN-supported beamforming using simulated data and ideal binary masks (IBM) are compared with another variant of NNsupported beamforming that is trained solely on the VOiCES data. Lack of data revealed by experiments with VOiCESdata trained beamformer was tackled by means of a variant of SpecAugment applied to magnitude spectra. This approach led to as much as 10% relative improvement in EER pushing results closer to those obtained by a good beamformer based on IBMs.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of Odyssey 2020 The Speaker and Language Recognition Workshop

ISBN

—

ISSN

2312-2846

e-ISSN

—

Počet stran výsledku

7

Strana od-do

187-193

Název nakladatele

International Speech Communication Association

Místo vydání

Tokyo

Místo konání akce

Tokyo

Datum konání akce

1. 11. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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