Introducing the VoicePrivacy initiative

Tomashenko, Natalia; Srivastava, Brij Mohan Lal; Wang, Xin; Vincent, Emmanuel; Nautsch, Andreas; Yamagishi, Junichi; Evans, Nicholas; Patino, Jose; Bonastre, Jean-François; Noé, Paul-Gauthier; Todisco, Massimiliano

Document type :

Communication dans un congrès avec actes

Title :

Introducing the VoicePrivacy initiative

Author(s) :

Tomashenko, Natalia [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Srivastava, Brij Mohan Lal [Auteur]
Machine Learning in Information Networks [MAGNET]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Wang, Xin [Auteur]
National Institute of Informatics [NII]
Vincent, Emmanuel [Auteur]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Nautsch, Andreas [Auteur]
Eurecom [Sophia Antipolis]
Yamagishi, Junichi [Auteur]
National Institute of Informatics [NII]
University of Edinburgh [Edin.]
Evans, Nicholas [Auteur]
Eurecom [Sophia Antipolis]
Patino, Jose [Auteur]
Eurecom [Sophia Antipolis]
Bonastre, Jean-François [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Noé, Paul-Gauthier [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Todisco, Massimiliano [Auteur]
Eurecom [Sophia Antipolis]

Conference title :

INTERSPEECH 2020

City :

Shanghai

Country :

Chine

Start date of the conference :

2020-10-25

English keyword(s) :

automatic speech recognition
speaker verification
voice conversion
anonymization
speech synthesis
privacy

HAL domain(s) :

Informatique [cs]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Cryptographie et sécurité [cs.CR]

English abstract : [en]

The VoicePrivacy initiative aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking ...
Show more >The VoicePrivacy initiative aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges. In this paper, we formulate the voice anonymization task selected for the VoicePrivacy 2020 Challenge and describe the datasets used for system development and evaluation. We also present the attack models and the associated objective and subjective evaluation metrics. We introduce two anonymization baselines and report objective evaluation results.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Clonage et protection de l'identité vocale
Apprentissage distribué, personnalisé, préservant la privacité pour le traitement de la parole
Open data, outils et challenges pour l'anonymisation des voix

Collections :