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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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Tomashenko, Natalia; Wang, Xin; Vincent, Emmanuel; Patino, Jose; Srivastava, Brij Mohan Lal; Noé, Paul-Gauthier; Nautsch, Andreas; Evans, Nicholas; Yamagishi, Junichi; O'brien, Benjamin; Chanclu, Anaïs; Bonastre, Jean-François; Todisco, Massimiliano; Maouche, Mohamed
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Abstract:
This paper presents the results and analyses stemming from the first VoicePrivacy 2020 Challenge which focuses on developing anonymization solutions for speech technology. We provide a systematic overview of the challenge design with an analysis of submitted systems and evaluation results. In particular, we describe the voice anonymization task and datasets used for system development and evaluation. Also, we present different attack models and the associated objective and subjective evaluation metrics. We introduce two anonymization baselines and provide a summary description of the anonymization systems developed by the challenge participants. We report objective and subjective evaluation results for baseline and submitted systems. In addition, we present experimental results for alternative privacy metrics and attack models developed as a part of the post-evaluation analysis. Finally, we summarise our insights and observations that will influence the design of the next VoicePrivacy challenge edition and some directions for future voice anonymization research.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; anonymization; attack model; automatic speech recognition; metrics; privacy; speaker verification; speech synthesis; utility; voice conversion
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URL: https://hal.archives-ouvertes.fr/hal-03332224v2/file/VoicePrivacyCSL_paper_hal2.pdf https://hal.archives-ouvertes.fr/hal-03332224v2/document https://hal.archives-ouvertes.fr/hal-03332224
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Benchmarking and challenges in security and privacy for voice biometrics
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In: SPSC 2021, 1st ISCA Symposium on Security and Privacy in Speech Communication ; https://hal.archives-ouvertes.fr/hal-03346196 ; SPSC 2021, 1st ISCA Symposium on Security and Privacy in Speech Communication, ISCA, Nov 2021, Magdeburg, Germany. ⟨10.21437/SPSC.2021-11⟩ ; https://spsc-symposium2021.de/#home (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Introducing the VoicePrivacy initiative
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In: INTERSPEECH 2020 ; https://hal.inria.fr/hal-02562199 ; INTERSPEECH 2020, Oct 2020, Shanghai, China (2020)
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The VoicePrivacy 2020 Challenge Evaluation Plan
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In: https://hal.archives-ouvertes.fr/hal-03623450 ; [Other] LIA - Laboratoire Informatique d'Avignon; MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery; Eurecom [Sophia Antipolis]; University of Edinburgh. 2020 (2020)
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