Erdel T, Crooks S
Cerner Corporation, Kansas City, Missouri, USA.
J Healthc Inf Manag. 2000 Summer;14(2):13-21.
Speech recognition, as an enabling technology in healthcare-systems computing, is a topic that has been discussed for quite some time, but is just now coming to fruition. Traditionally, speech-recognition software has been constrained by hardware, but improved processors and increased memory capacities are starting to remove some of these limitations. With these barriers removed, companies that create software for the healthcare setting have the opportunity to write more successful applications. Among the criticisms of speech-recognition applications are the high rates of error and steep training curves. However, even in the face of such negative perceptions, there remains significant opportunities for speech recognition to allow healthcare providers and, more specifically, physicians, to work more efficiently and ultimately spend more time with their patients and less time completing necessary documentation. This article will identify opportunities for inclusion of speech-recognition technology in the healthcare setting and examine major categories of speech-recognition software--continuous speech recognition, command and control, and text-to-speech. We will discuss the advantages and disadvantages of each area, the limitations of the software today, and how future trends might affect them.
语音识别作为医疗系统计算中的一项使能技术,是一个已经讨论了相当一段时间但才刚刚开始取得成果的话题。传统上,语音识别软件受到硬件的限制,但处理器的改进和内存容量的增加开始消除其中一些限制。随着这些障碍的消除,为医疗环境创建软件的公司有机会编写更成功的应用程序。对语音识别应用的批评包括错误率高和训练曲线陡峭。然而,即使面对这种负面看法,语音识别仍有巨大机会让医疗服务提供者,更具体地说是医生,工作得更高效,最终有更多时间陪伴患者,而花在完成必要文档上的时间更少。本文将确定在医疗环境中纳入语音识别技术的机会,并研究语音识别软件的主要类别——连续语音识别、命令与控制以及文本转语音。我们将讨论每个领域的优缺点、当今软件的局限性以及未来趋势可能如何影响它们。