一个大规模的PCR参考语音音频数据集用于COVID-19
Jobie Budd1,2, Kieran Baker3,4, Emma Karoune5
1London Centre for Nanotechnology, University College London, London, UK.
Scientific data
|June 27, 2024
概括
这项研究介绍了英国的COVID-19语音音频数据集,这是最大的SARS-CoV-2PCR参考音频录音集合. 它使机器学习模型能够从语音数据中检测感染和呼吸系统症状.
科学领域:
- 生物医学信息学 生物医学信息学
- 数据科学数据科学数据科学
- 生物声学是一种生物声学.
背景情况:
- 由于COVID-19的流行,需要创新的诊断工具.
- 语音音频分析提供了一种非侵入性方法来检测呼吸系统疾病.
- 大量的,具有良好的特征的数据集对于开发强大的机器学习模型至关重要.
研究的目的:
- 创建和描述英国COVID-19声乐音频数据集.
- 为了促进机器学习模型的开发,用于使用语音音频检测SARS-CoV-2感染.
- 为研究呼吸系统症状和生物声学提供资源.
主要方法:
- 通过英国的国家计划 (测试和追踪,REACT-1) 招募志愿参与者.
- 收集音频录音 (咳,呼气,言语) 和相关的人口,症状和呼吸系统状况数据.
- 将音频数据与SARS-CoV-2聚合酶链反应 (PCR) 测试结果联系起来.
主要成果:
- 数据集包括72,999名参与者,有70,565个链接PCR结果.
- 包括25,706个COVID-19阳性病例,其中24,105个是PCR结果.
- 45.6%的参与者报告了呼吸系统症状;11.3%报告了喘;27.2%的参与者报告了流感PCR结果.
结论:
- 英国COVID-19语音音频数据集是迄今为止针对SARS-CoV-2研究的最大的PCR参考语音音频集合.
- 该数据集支持机器学习模型的开发,用于分类感染状态和呼吸系统症状.
- 潜在的应用范围扩展到生物声学研究和了解喘和流感等呼吸系统疾病.
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