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为医疗对话开发ASR系统

Alejandro Renato¹, Daniel Luna¹, Sonia Benítez¹

¹Department of Helth Informatics, Hospital Italiano de Buenos Aires.

Studies in health technology and informatics

|January 25, 2024

概括

一个用于患者与医生的对话的新自动语音识别 (ASR) 系统在远程咨询中实现了72.5%的准确性. 它还在承认医疗实体方面表现强,F1得分为0.80.

科学领域:

医疗信息学医疗信息学
计算语言学计算语言学
语音技术语言技术

背景情况:

准确的患者与医生的对话转录对于医疗记录和分析至关重要.
现有的自动语音识别 (ASR) 系统可能会在医疗远程咨询的专业语言和声学条件下扎.

研究的目的:

开发和评估一个针对患者与医生的远程咨询而定制的特定领域的ASR系统.
将开发系统的性能与已建立的ASR解决方案进行比较.

主要方法:

该系统使用自发语音声学基础,域特定语言模型和监督语音字典进行了训练.
在2020年记录的208次远程咨询中评估了绩效.
这些指标包括ASR的文字错误率 (WER) 和医疗实体识别的召回/F1.

主要成果:

开发的ASR系统在远程咨询领域实现了72.5%的准确性.
该系统获得了医疗实体认可的F1分数为0.80.
它在西班牙语和谷歌APIASR云中的NeMo端到端兼容器和谷歌APIASR云中都表现出色.

结论:

开发的特定领域的ASR系统在转录患者-医生远程咨询方面表现出卓越的性能.
与一般的ASR工具相比,该系统提供了更好的准确性和医疗实体识别功能.
这些发现强调了ASR在专业应用中域调整的重要性.

关键词:

自动语音识别自动语音识别人工智能的人工智能是人工智能.人与计算机的互动.自然语言处理自然语言处理.远程医疗远程医疗

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