Detecting and tracking alertness using speech biometrics

使用语音生物识别技术检测和跟踪警觉性

• 批准号: FT220100253
• 负责人: Prof Adam Vogel
• 金额: $ 73.13万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT220100253
• 关键词: Detecting; tracking; alertness; using; speech

Traditional tests for detecting and tracking alertness are limited by their accuracy and inability to be administered without stopping work. This project aims to investigate how speech can be used to monitor changes in performance resulting from sleep deprivation and successive night shifts. The expected outcomes are 1) new knowledge on how sensitive speech and language features are for detecting change in alertness, and 2) development and verification of a highly accurate, cost-effective, speech focussed assay capable of detecting impaired alertness from otherwise healthy individuals. The project should benefit the way fitness for duty is tested and provide new methods for safeguarding Australians working in at-risk environments.

传统的检测和跟踪警觉性的测试受其准确性和不能在不停止工作的情况下进行管理的限制。该项目旨在研究如何利用语言来监测由于睡眠剥夺和连续夜班而导致的表现变化。预期的结果是：1)关于语言和语言特征在检测警觉性变化方面有多敏感的新知识；2)开发和验证一种高度准确、成本效益高、以语言为重点的检测方法，能够检测其他健康个体的警觉性受损。该项目将有利于测试工作能力的方式，并为保护在危险环境中工作的澳大利亚人提供新的方法。