Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information

The human voice contains complex acoustic markers which have been linked to important health conditions including dementia, mood disorders, and cancer. When viewed as a biomarker, voice is a promising characteristic to measure as it is simple to collect, cost-effective, and has broad clinical utility. Recent advances in artificial intelligence have provided techniques to extract previously unknown prognostically useful information from dense data elements such as images. The Bridge2AI-Voice project seeks to create an ethically sourced flagship dataset to enable future research in artificial intelligence and support critical insights into the use of voice as a biomarker of health. Here we present Bridge2AI-Voice, a comprehensive collection of data derived from voice recordings with corresponding clinical information. Bridge2AI-Voice v1.0, the initial release, provides 12,523 recordings for 306 participants collected across five sites in North America. Participants were selected based on known conditions which manifest within the voice waveform including voice disorders, neurological disorders, mood disorders, and respiratory disorders. The initial release contains data considered low risk, including derivations such as spectrograms but not the original voice recordings. Detailed demographic, clinical, and validated questionnaire data are also made available.

人类语音中蕴含着复杂的声学特征，这些特征与包括痴呆症、情绪障碍和癌症在内的多种重要健康问题相关联。将语音视为生物标志物时，它因其易于收集、成本效益高以及广泛的临床应用价值而成为一项极具潜力的特性。近年来，人工智能技术的进步为从密集的数据元素，如图像中提取先前未知且具有预后价值的信息提供了技术手段。Bridge2AI-Voice项目旨在创建一个道德来源的旗舰数据集，以促进人工智能未来的研究，并支持对语音作为健康生物标志物应用的深入洞察。在此，我们介绍了Bridge2AI-Voice，这是一个由语音录音和相关临床信息衍生出的全面数据集。Bridge2AI-Voice v1.0作为首个版本，提供了306位参与者在美国五大站点收集的12,523段录音。参与者基于语音波形中显现的已知条件进行选择，包括语音障碍、神经系统障碍、情绪障碍和呼吸系统障碍。初始发布包含被认为是低风险的数据，包括频谱图等衍生数据，但不包括原始语音录音。此外，还提供了详细的人口统计、临床和经过验证的问卷数据。