在临床研究的语音匿名化中,在个人隐私和数据实用性之间进行权衡
Catherine Diaz-Asper1,2, Lars Ailo Bongo3, Brita Elvevåg4
1Department of Psychology, Marymount University, Arlington, VA, USA. cdiazasp@marymount.edu.
NPJ digital medicine
|October 17, 2025
概括
匿名语音数据用于临床研究涉及平衡隐私和数据实用性. 像概括和扰乱这样的常用方法在保存分析的基本语音特征方面存在挑战.
科学领域:
- 生物信息学是一种生物信息学.
- 语音处理 语音处理
- 数据 隐私 数据 隐私 数据
背景情况:
- 语音数据包含敏感的个人身份信息.
- 匿名化对于保护临床研究中的隐私至关重要.
- 现有的匿名化技术往往会损害数据的实用性.
研究的目的:
- 检查语音数据匿名化中的隐私-实用性权衡.
- 突出在保持临床研究分析数据实用性的挑战.
- 评估常见的匿名化技术.
主要方法:
- 复习常见的匿名化技术:一般化,抑制,解剖化,变换和扰乱.
- 分析这些技术对语音数据实用性的影响.
- 在临床研究中,专注于个人级别的语音数据分析.
主要成果:
- 匿名化策略本质上涉及隐私保护和数据实用性之间的权衡.
- 一般化,抑制,解剖化,变换和扰乱都带来了独特的挑战.
- 保持临床分析的基本语音特征在当前的方法中是困难的.
结论:
- 对于临床研究而言,语音数据的有效匿名化需要仔细考虑隐私与实用性的平衡.
- 需要进一步的研究来开发改进的匿名化技术.
- 目前的方法对详细的语音数据分析有重大局限性.
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