针对多人对话中仅匿名特定说话人提出新方法与评估标准
Target speaker anonymization in multi-speaker recordings
- 聚焦多人对话中仅匿名指定说话人的难题，设计针对性方案
- 揭示现有方法在多说话人场景下的隐私保护不足问题
- 提出适用于此类场景的新评估框架，兼顾隐私与语音可用性
现有说话人匿名化研究主要针对单说话人音频，发展出相应技术与评估指标。本文解决多说话人对话音频中仅需匿名特定目标说话人这一关键挑战，该场景在客服中心等场景中极为常见，需仅保护客户语音隐私。传统方法难以适用，且当前评估体系无法准确衡量此类复杂场景下的隐私保护程度与语音可用性。本研究旨在填补空白，探索有效的目标说话人匿名化策略，指出其开发中的潜在问题，并提出改进的评估方法。
原文摘要 · Abstract (English)
Most of the existing speaker anonymization research has focused on single-speaker audio, leading to the development of techniques and evaluation metrics optimized for such condition. This study addresses the significant challenge of speaker anonymization within multi-speaker conversational audio, specifically when only a single target speaker needs to be anonymized. This scenario is highly relevant in contexts like call centers, where customer privacy necessitates anonymizing only the customer's voice in interactions with operators. Conventional anonymization methods are often not suitable for this task. Moreover, current evaluation methodology does not allow us to accurately assess privacy protection and utility in this complex multi-speaker scenario. This work aims to bridge these gaps by exploring effective strategies for targeted speaker anonymization in conversational audio, highlighting potential problems in their development and proposing corresponding improved evaluation methodologies.
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