评估成人语音匿名技术在儿童语音上的效果，发现隐私保护有效但音质损失大。
Children's Voice Privacy: First Steps And Emerging Challenges
- 用六个成人语音匿名方法测试儿童语音数据集
- 成人技术可保护儿童语音隐私，但音质下降明显
- 自动评估方法对儿童语音不准确，需新研究
儿童是语音技术中代表性不足且隐私最脆弱的群体之一。尽管如此，针对这一群体的语音匿名化研究仍很少。本研究旨在填补这一空白，建立将成人语音匿名技术应用于儿童语音的基准。研究包含三个儿童语音数据集、六种匿名化方法，并采用客观与主观评估指标。结果表明，现有成人语音匿名系统虽能有效保护儿童语音隐私，但存在显著的语音质量退化。此外，主观实验揭示了当前自动语音质量评估方法在儿童语音场景下的局限性，凸显了进一步研究的必要性。
原文摘要 · Abstract (English)
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenges when compared to that of adults. This study comprises three children's datasets, six anonymization methods, and objective and subjective utility metrics for evaluation. Our results show that existing systems for adults are still able to protect children's voice privacy, but suffer from much higher utility degradation. In addition, our subjective study displays the challenges of automatic evaluation methods for speech quality in children's speech, highlighting the need for further research.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。