2024年语音人工智能研讨会的研讨会摘要,由Bridge2AI-语音联盟提出
Ruth Bahr1, James Anibal2,3, Steven Bedrick4
1Department of Communication Sciences & Disorders, University of South Florida, Tampa, FL, United States.
Frontiers in digital health
|November 14, 2024
概括
2024年语音人工智能研讨会在医疗保健领域推进了语音生物标志物和人工智能 (AI). 专家们讨论了声数据的标准化,部署人工智能解决方案以及改善诊断和治疗的伦理人工智能实践.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 人工智能的人工智能
- 生物医学工程 生物医学工程
背景情况:
- 2024年语音人工智能研讨会召开专家会议,讨论语音生物标志物和人工智能应用方面的进展.
- 研讨会涵盖了国际标准化,现实世界的AI部署,辅助技术,数据收集和语音分析的深度学习.
研究的目的:
- 促进学术界,工业界和医疗保健界之间的合作.
- 推进医疗保健中基于语音的AI工具的开发和实施.
- 探索语音生物标志物和人工智能的最新创新.
主要方法:
- 五个教育研讨会,包括讲座,案例研究和互动讨论.
- 使用Whisper生成的音频录制成绩单,并通过ChatGPT进行总结.
- 探索包括信号处理,机器学习操作 (MLOps) 和道德考虑在内的方法.
主要成果:
- 讨论声部生物标志物研究的国际标准和实际部署的挑战.
- 审查数据收集过程和人工智能在语音障碍管理方面的潜力.
- 强调道德AI,可扩展机器学习和健康应用的多样化语音数据集的进步.
结论:
- 跨学科的合作对于解决语音生物标志物的技术,伦理和临床挑战至关重要.
- 人工智能在语音数据分析方面表现有前途,但数据变化,安全性和可扩展性需要进一步关注.
- 未来的努力应该集中在完善数据标准,伦理实践和多样化的数据集,以提高医疗保健中的AI模型的稳定性.
关键词:
桥梁2AIAI 的时间桥梁2AI-声音人工智能的人工智能是人工智能.人工智能AI 的人工智能AI音频传感器 音频传感器伦理的人工智能语音生物标志物是一种生物标志物.语音生物标志物语音生物标志物更多相关视频
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