Integration of speech into healthcare has intensified privacy concerns due to its potential as a non-invasive biomarker containing individual biometric information. In response, speaker anonymization aims to conceal personally identifiable information while retaining crucial linguistic content. However, the application of anonymization techniques to pathological speech, a critical area where privacy is especially vital, has not been extensively examined. This study investigates anonymization's impact on pathological speech across over 2,700 speakers from multiple German institutions, focusing on privacy, pathological utility, and demographic fairness. We explore both deep-learning-based and signal processing-based anonymization methods, and document substantial privacy improvements across disorders-evidenced by equal error rate increases up to 1933%, with minimal overall impact on utility. Specific disorders such as Dysarthria, Dysphonia, and Cleft Lip and Palate experienced minimal utility changes, while Dysglossia showed slight improvements. Our findings underscore that the impact of anonymization varies substantially across different disorders. This necessitates disorder-specific anonymization strategies to optimally balance privacy with diagnostic utility. Additionally, our fairness analysis revealed consistent anonymization effects across most of the demographics. This study demonstrates the effectiveness of anonymization in pathological speech for enhancing privacy, while also highlighting the importance of customized and disorder-specific approaches to account for inversion attacks.

翻译：将语音整合到医疗保健领域加剧了隐私担忧，因为语音作为一种非侵入性生物标志物，包含个体生物特征信息。为此，说话人匿名化旨在隐藏个人可识别信息，同时保留关键的语言内容。然而，匿名化技术在病理语音这一隐私尤为关键的重要领域的应用尚未得到广泛研究。本研究调查了匿名化对来自多个德国机构的2700多名说话者的病理语音的影响，重点关注隐私性、病理效用和人口统计学公平性。我们探索了基于深度学习和基于信号处理的匿名化方法，并记录了跨多种障碍的隐私性显著提升——等错误率最高增加1933%，同时对整体效用的影响极小。特定障碍如构音障碍、发声障碍和唇腭裂的效用变化极小，而构音异常则显示出轻微改善。我们的研究结果强调，匿名化的影响在不同障碍之间存在显著差异。这需要针对特定障碍制定匿名化策略，以在隐私和诊断效用之间实现最佳平衡。此外，我们的公平性分析显示，匿名化效果在大多数人口统计学特征上保持一致。本研究证明了匿名化在病理语音中提升隐私的有效性，同时也强调了采用定制化和针对特定障碍的方法以应对反转攻击的重要性。