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对于紧急医疗服务的环境稳健的语音助理系统
Zhenchuan Zhang1, Yu Tian2, Tianshu Zhou1
1Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China.
Studies in health technology and informatics
|January 25, 2024
概括
本研究引入了个性化语音增强 (PSE) 方法,以改善紧急诊所医生的自动语音识别. 该PSE系统有效地减少背景噪音和重叠的语音在医院前设置,提高系统的准确性.
科学领域:
- 生物医学工程 生物医学工程
- 语音技术 语言技术
- 紧急医疗 紧急医疗
背景情况:
- 自动语音识别 (ASR) 系统对于急诊临床医生至关重要,但在医院前设置中,它们与环境干扰作斗争.
- 背景噪音和重叠的语音显著降低了急诊医疗服务 (EMS) 中的ASR性能.
- 现有的ASR解决方案缺乏应急护理的动态和杂环境所需的稳定性.
研究的目的:
- 为紧急诊所医生开发一个环境友好的语音助理系统.
- 引入个性化语音增强 (PSE) 方法,以改善噪音较大的医院前环境中的ASR.
- 通过改进语音识别来提高紧急医疗服务的效率和安全性.
主要方法:
- 开发了一个个性化的语音增强 (PSE) 方法,利用目标医生的语音印记.
- 实施了一个系统来抑制非目标信号组件,包括背景噪音和重叠的语音.
- 通过使用客观语音质量指标 (DNSMOS) 和在一般和真实EMS测试集上的识别精度来评估系统的性能.
主要成果:
- 拟议的PSE方法在提高语音质量和识别准确性方面显示出显著的潜力.
- 客观评估显示,在一般公众和现实世界的EMS测试数据集上,性能有所改善.
- 该系统有效地抑制了环境干扰,这是医院前ASR的一个关键挑战.
结论:
- 个性化语音增强 (PSE) 方法为在具有挑战性的医院前环境中提供了强大的ASR的可行解决方案.
- 这项技术有可能提高紧急医疗服务的效率和安全性.
- 进一步开发和实施PSE可以显著有利于紧急诊所的医生,他们依赖于基于语音的技术.
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