ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale

Authors

Kong Aik Lee (ORCID: https://orcid.org/0000-0001-9133-3000)
Junichi Yamagishi (ORCID: https://orcid.org/0000-0003-2752-3955)
Xuechen Liu (ORCID: https://orcid.org/0000-0003-1207-5651)
Hemlata Tak (ORCID: https://orcid.org/0000-0002-0102-523X)
Tomi Kinnunen (ORCID: https://orcid.org/0000-0002-4371-7322)
Massimiliano Todisco (ORCID: https://orcid.org/0000-0003-2883-0324)
Nicholas Evans (ORCID: https://orcid.org/0000-0002-8459-1041)
Héctor Delgado (ORCID: https://orcid.org/0000-0002-4475-2517)
Md Sahidullah (ORCID: https://orcid.org/0000-0002-0624-2903)
Hye-jin Shim (ORCID: https://orcid.org/0000-0002-0912-6983)
Ivan Kukanov (ORCID: https://orcid.org/0000-0003-4052-2754)
Jee-weon Jung (ORCID: https://orcid.org/0000-0003-0505-2988)
Xin Wang

Institutions

EURECOM (FR)

Publication Details

Published: 2024-08-31
DOI: https://doi.org/10.21437/asvspoof.2024-1
Citations: 42
Primary Topic: Adversarial Robustness in Machine Learning
Type: article
Field-Weighted Citation Impact: 14.59

Funders

Itä-Suomen Yliopisto
Helsingin Yliopisto
Carnegie Mellon University
University of Rochester
Agence Nationale de la Recherche
Academia Sinica
Seoul National University
Renmin University of China
Tianjin University
National Taiwan University
University of Science and Technology of China
Universität Stuttgart
University at Buffalo
Precursory Research for Embryonic Science and Technology

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article

ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale

Kong Aik Lee, Junichi Yamagishi, Xuechen Liu, Hemlata Tak et al.

Aug 31, 2024

42 citations

Adversarial Robustness in Machine Learning

14.59

article

ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale

Kong Aik Lee, Junichi Yamagishi, Xuechen Liu, Hemlata Tak, Tomi Kinnunen, Massimiliano Todisco, Nicholas Evans, Héctor Delgado, Md Sahidullah, Hye-jin Shim, Ivan Kukanov, Jee-weon Jung, Xin Wang

August 31, 2024article en

42 citations

Abstract

No abstract available for this paper.

EURECOM (FR)

Itä-Suomen Yliopisto, Helsingin Yliopisto, Carnegie Mellon University, University of Rochester, Agence Nationale de la Recherche, Academia Sinica, Seoul National University, Renmin University of China, Tianjin University, National Taiwan University, University of Science and Technology of China, Universität Stuttgart, University at Buffalo, Precursory Research for Embryonic Science and Technology

Gender equality

Openalex Percentile: Top 1%

Adversarial Robustness in Machine Learning

14.59

DOI Open Access PDF OpenAlex

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