The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization

Fuente: arXiv
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Main Authors: Tomashenko, Natalia, Miao, Xiaoxiao, Champion, Pierre, Meyer, Sarina, Panariello, Michele, Wang, Xin, Evans, Nicholas, Vincent, Emmanuel, Yamagishi, Junichi, Todisco, Massimiliano
Format: Preprint
Published: 2026
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author Tomashenko, Natalia
Miao, Xiaoxiao
Champion, Pierre
Meyer, Sarina
Panariello, Michele
Wang, Xin
Evans, Nicholas
Vincent, Emmanuel
Yamagishi, Junichi
Todisco, Massimiliano
author_facet Tomashenko, Natalia
Miao, Xiaoxiao
Champion, Pierre
Meyer, Sarina
Panariello, Michele
Wang, Xin
Evans, Nicholas
Vincent, Emmanuel
Yamagishi, Junichi
Todisco, Massimiliano
contents We present results and analyses from the third VoicePrivacy Challenge held in 2024, which focuses on advancing voice anonymization technologies. The task was to develop a voice anonymization system for speech data that conceals a speaker's voice identity while preserving linguistic content and emotional state. We provide a systematic overview of the challenge framework, including detailed descriptions of the anonymization task and datasets used for both system development and evaluation. We outline the attack model and objective evaluation metrics for assessing privacy protection (concealing speaker voice identity) and utility (content and emotional state preservation). We describe six baseline anonymization systems and summarize the innovative approaches developed by challenge participants. Finally, we provide key insights and observations to guide the design of future VoicePrivacy challenges and identify promising directions for voice anonymization research.
format Preprint
id arxiv_https___arxiv_org_abs_2601_11846
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization
Tomashenko, Natalia
Miao, Xiaoxiao
Champion, Pierre
Meyer, Sarina
Panariello, Michele
Wang, Xin
Evans, Nicholas
Vincent, Emmanuel
Yamagishi, Junichi
Todisco, Massimiliano
Computation and Language
Sound
Audio and Speech Processing
We present results and analyses from the third VoicePrivacy Challenge held in 2024, which focuses on advancing voice anonymization technologies. The task was to develop a voice anonymization system for speech data that conceals a speaker's voice identity while preserving linguistic content and emotional state. We provide a systematic overview of the challenge framework, including detailed descriptions of the anonymization task and datasets used for both system development and evaluation. We outline the attack model and objective evaluation metrics for assessing privacy protection (concealing speaker voice identity) and utility (content and emotional state preservation). We describe six baseline anonymization systems and summarize the innovative approaches developed by challenge participants. Finally, we provide key insights and observations to guide the design of future VoicePrivacy challenges and identify promising directions for voice anonymization research.
title The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization
topic Computation and Language
Sound
Audio and Speech Processing
url https://arxiv.org/abs/2601.11846