Supplementary material to the paper The ...
Type de document :
Pré-publication ou Document de travail
URL permanente :
Titre :
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
Auteur(s) :
Tomashenko, Natalia [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Wang, Xin [Auteur]
National Institute of Informatics [NII]
Vincent, Emmanuel [Auteur]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Patino, Jose [Auteur]
Eurecom [Sophia Antipolis]
Srivastava, Brij Mohan Lal [Auteur]
Machine Learning in Information Networks [MAGNET]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Noé, Paul-Gauthier [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Nautsch, Andreas [Auteur]
Eurecom [Sophia Antipolis]
Evans, Nicholas [Auteur]
Eurecom [Sophia Antipolis]
Yamagishi, Junichi [Auteur]
National Institute of Informatics [NII]
University of Edinburgh [Edin.]
O'brien, Benjamin [Auteur]
Laboratoire Parole et Langage [LPL]
Chanclu, Anaïs [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Bonastre, Jean-François [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Todisco, Massimiliano [Auteur]
Eurecom [Sophia Antipolis]
Maouche, Mohamed [Auteur]
Machine Learning in Information Networks [MAGNET]
Laboratoire Informatique d'Avignon [LIA]
Wang, Xin [Auteur]
National Institute of Informatics [NII]
Vincent, Emmanuel [Auteur]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Patino, Jose [Auteur]
Eurecom [Sophia Antipolis]
Srivastava, Brij Mohan Lal [Auteur]
Machine Learning in Information Networks [MAGNET]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Noé, Paul-Gauthier [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Nautsch, Andreas [Auteur]
Eurecom [Sophia Antipolis]
Evans, Nicholas [Auteur]
Eurecom [Sophia Antipolis]
Yamagishi, Junichi [Auteur]
National Institute of Informatics [NII]
University of Edinburgh [Edin.]
O'brien, Benjamin [Auteur]
Laboratoire Parole et Langage [LPL]
Chanclu, Anaïs [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Bonastre, Jean-François [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Todisco, Massimiliano [Auteur]
Eurecom [Sophia Antipolis]
Maouche, Mohamed [Auteur]
Machine Learning in Information Networks [MAGNET]
Mot(s)-clé(s) en anglais :
speaker verification
voice conversion
automatic speech recognition
attack model
metrics
utility
privacy
anonymization
speech synthesis
voice conversion
automatic speech recognition
attack model
metrics
utility
privacy
anonymization
speech synthesis
Discipline(s) HAL :
Informatique [cs]/Intelligence artificielle [cs.AI]
Résumé en anglais : [en]
The VoicePrivacy 2020 Challenge focuses on developing anonymization solutions for speech technology. This report complements the summary results and analyses presented by Tomashenko et al. (2021). After quickly recalling ...
Lire la suite >The VoicePrivacy 2020 Challenge focuses on developing anonymization solutions for speech technology. This report complements the summary results and analyses presented by Tomashenko et al. (2021). After quickly recalling the challenge design and the submitted anonymization systems, we provide more detailed results and analyses. First, we present objective evaluation results for the primary challenge metrics and for alternative metrics and attack models, and we compare them with each other. Second, we present subjective evaluation results for speaker verifiability, speech naturalness, and speech intelligibility. Finally, we compare these objective and subjective evaluation results with each other.Lire moins >
Lire la suite >The VoicePrivacy 2020 Challenge focuses on developing anonymization solutions for speech technology. This report complements the summary results and analyses presented by Tomashenko et al. (2021). After quickly recalling the challenge design and the submitted anonymization systems, we provide more detailed results and analyses. First, we present objective evaluation results for the primary challenge metrics and for alternative metrics and attack models, and we compare them with each other. Second, we present subjective evaluation results for speaker verifiability, speech naturalness, and speech intelligibility. Finally, we compare these objective and subjective evaluation results with each other.Lire moins >
Langue :
Anglais
Projet ANR :
Commentaire :
Supplementary material to the paper "The VoicePrivacy 2020 Challenge: Results and findings" (https://hal.archives-ouvertes.fr/hal-03332224) submitted to CSL.
Collections :
Source :
Date de dépôt :
2021-11-13T02:07:16Z
Fichiers
- https://hal.archives-ouvertes.fr/hal-03335126v3/document
- Accès libre
- Accéder au document