The VoicePrivacy 2020 Challenge Evaluation Plan

Natalia Tomashenko (1) , Brij Mohan Lal Srivastava (2, 3) , Xin Wang (4) , Emmanuel Vincent (3) , Andreas Nautsch (5) , Junichi Yamagishi (4) , Nicholas Evans (5) , Jose Patino (5) , Jean-François 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]

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.

Domaines: Informatique [cs]

Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, et al.. The VoicePrivacy 2020 Challenge Evaluation Plan. [0] 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. ⟨hal-03623450v2⟩