Joint speaker encoder and neural back-end model for fully end-to-end automatic speaker verification with multiple enrollment utterances-Reference-Cited by-同舟云学术

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Joint speaker encoder and neural back-end model for fully end-to-end automatic speaker verification with multiple enrollment utterances

Published:2024-06 Issue: Volume:86 Page:101619
ISSN:0885-2308
Container-title:Computer Speech & Language
language:en
Short-container-title:Computer Speech & Language

Author:

Zeng Chang^ORCID,Miao Xiaoxiao^ORCID,Wang Xin^ORCID,Cooper Erica^ORCID,Yamagishi Junichi^ORCID

Funder

Japan Society for the Promotion of Science

Japan Science and Technology Agency

Core Research for Evolutional Science and Technology

Publisher

Elsevier BV

Reference68 articles.

1. TristouNet: Triplet loss for speaker turn embedding;Bredin,2017

2. In defence of metric learning for speaker recognition;Chung,2020

3. VoxCeleb2: Deep speaker recognition;Chung,2018

4. Joint estimation of PLDA and nonlinear transformations of speaker vectors;Cumani;IEEE/ACM Trans. Audio Speech Lang. Process.,2017

5. Front-end factor analysis for speaker verification;Dehak;IEEE Trans. Audio Speech Lang. Process.,2010

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