利用语音系统为医疗保健行业提供有效的语音识别功能

Gulbakshee J. Dharmale, Dipti D. Patil, Tanaya Ganguly, Nitin Shekapure
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引用次数: 0

摘要

自动语音识别有助于实现当今的需求,如病人护理的灵活性、效率和医疗记录。自动语音识别可以更有效地使用和组合流程管理设备和系统。由于语音交互是非接触式的,它们可以无缝地结合到当前的硬件环境中。本文介绍的语音系统旨在提高自动语音识别的准确性,从而提高性能。该系统通过麦克风获取输入语音,然后对所试语音进行识别。然后,它将随后的文本传递给 HMM 分类器。HMM 分类器根据概率图比较认可单词的出现率。选出出现概率最高的单词。然后,它用这个词替换认可的词;这一过程在整个认可文本中进行。语音系统直接获取语音并将其翻译成文本,使系统的准确率提高了 8%。利用语音系统开发的独立于文本的智能多语言短信系统允许用户将语音转换为文本并发送信息。STIM 短信系统可以很好地替代传统键盘。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective speech recognition for healthcare industry using phonetic system
The automatic speech recognition helps to achieve today’s demands such as flexibility in patient care, efficiency, medical records. ASR allows more effective use and combination of process management devices and systems. Because speech interaction is contactless, they can be seamlessly combined into a current hardware environment. This paper presents the phonetic system that implemented to improve the automatic speech recognition with higher accuracy for increasing performance. The system obtains input speech by a mic then works on the tried speech to recognize the spoken word. After that, it passes the ensuing text to the HMM classifier. The HMM classifier compares occurrence of the accredited word with probability map. The word with the highest probability of occurrence gets selected. It then substitutes accredited word with this utterance; this process is carried out for the entire accredited text. The phonetic system directly obtains and translates speech to text by providing 8% improvement in the accuracy of the system. Smart text independent multi-lingual SMS system is developed using phonetic system, which allows the user to convert their voice into text and send message. STIM SMS system can offer a very spirited substitute to traditional keyboard.
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