The VoicePrivacy 2020 Challenge Evaluation Plan
Type de document :
Rapport de recherche
Titre :
The VoicePrivacy 2020 Challenge Evaluation Plan
Auteur(s) :
Tomashenko, Natalia [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Srivastava, Brij Mohan Lal [Auteur]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Machine Learning in Information Networks [MAGNET]
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]
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]
Laboratoire Informatique d'Avignon [LIA]
Srivastava, Brij Mohan Lal [Auteur]
Speech Modeling for Facilitating Oral-Based Communication [MULTISPEECH]
Machine Learning in Information Networks [MAGNET]
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]
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]
Institution :
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
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
Date de publication :
2020-02
Discipline(s) HAL :
Informatique [cs]
Résumé en anglais : [en]
The VoicePrivacy Challenge 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 ...
Lire la suite >The VoicePrivacy Challenge 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 document, 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.Lire moins >
Lire la suite >The VoicePrivacy Challenge 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 document, 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.Lire moins >
Langue :
Anglais
Projet ANR :
Collections :
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- https://hal.archives-ouvertes.fr/hal-03623450v2/document
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- https://hal.archives-ouvertes.fr/hal-03623450v2/document
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- https://hal.archives-ouvertes.fr/hal-03623450v2/document
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- Challenge_2020_HAL%2B.pdf
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