Introducing the VoicePrivacy initiative

Natalia Tomashenko (1) , Brij Mohan Lal Srivastava (2, 3) , Xin Wang (4) , Emmanuel Vincent (3) , Andreas Nautsch (5) , Junichi Yamagishi (4, 6) , Nicholas Evans (5) , Jose Patino (5) , J.-F Bonastre (1) , Paul-Gauthier Noé (1) , Massimiliano Todisco (5)

1 LIA - Laboratoire Informatique d'Avignon
2 MAGNET - Machine Learning in Information Networks
3 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
4 NII - National Institute of Informatics
5 Eurecom [Sophia Antipolis]
6 Edin. - University of Edinburgh

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.

Mots clés: privacy; anonymization; speech synthesis; voice conversion; speaker verification; automatic speech recognition

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

Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, et al.. Introducing the VoicePrivacy initiative. 2020. ⟨hal-02562199v1⟩