让语音匿名化同时保留说话内容和情绪，防止身份泄露。
The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization
- 设计系统在隐藏声音身份的同时保留语言与情绪信息。
- 采用多维度评估标准，兼顾隐私保护与语音可用性。
- 适合关注语音安全与人机交互的研究者与开发者。
我们介绍了2024年第三届语音隐私挑战赛的结果与分析，聚焦于推进语音匿名化技术的发展。任务要求开发一种语音匿名化系统，能够在隐藏说话人声纹身份的同时，保留语言内容和情感状态。本文系统性地概述了挑战赛框架，包括匿名化任务定义、用于系统开发与评估的数据集、攻击模型以及隐私保护（隐藏说话人身份）与实用性（内容与情感状态保留）的客观评价指标。我们介绍了六种基线匿名化系统，并总结了参赛者提出的创新方法。最后，我们提供了关键洞见与观察，为未来语音隐私挑战赛的设计提供指导，并指明了语音匿名化研究的潜在方向。
原文摘要 · Abstract (English)
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.
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