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玻璃体视网膜手术中的自动语音识别。一个基于计算机的原型语音控制玻璃体切割手术机器项目。

Automatic speech recognition in vitreo-retinal surgery. A project for a prototypal computer-based voice-controlled vitrectomy machine.

作者信息

Rossi L, Sacerdoti D, Billi B, Lesnoni G, Orciuolo M, Rossi T, Sacerdoti D, Bertollini L

机构信息

Department of Electronic Engineering, University of Roma La Sapienza, Italy.

出版信息

Eur J Ophthalmol. 1996 Oct-Dec;6(4):454-9. doi: 10.1177/112067219600600420.

Abstract

In the past half decade automatic speech recognition techniques, software and hardware technology have matured enough to support sophisticated medical applications. The project described aimed at introducing a computer-based, voice-controlled prototype system in a simulated vitreo-retinal surgery scenario. The aim was to provide the surgeon with a tool that could significantly improve the quality and ease of work and shorten the duration of intervention. The speech recognition system allows voice entry of simple commands to simulate surgical instrument control, including the infusion pump, vitreous cutter and diathermy. The project relies on a Markov-based, speaker-dependent, commercial isolated-word recognizer, and consists of a specific recognition vocabulary and application software, created and developed by the authors. Results have been encouraging. The system performed well under the test conditions, proving robust, simple to use and accurate (over 97% average word recognition rate). On the basis of their experience, the authors believe that automatic speech recognition technology, though suffering from some limitations such as the need for training, speaker dependence and a relatively small vocabulary, and requiring extensive testing under operating conditions, merits further development and opens new perspectives for a possible new generation of surgical instruments.

摘要

在过去的五年里,自动语音识别技术、软件和硬件技术已经足够成熟,能够支持复杂的医学应用。所描述的项目旨在在模拟玻璃体视网膜手术场景中引入一个基于计算机的语音控制原型系统。其目的是为外科医生提供一种工具,能够显著提高工作质量和便利性,并缩短干预时间。语音识别系统允许通过语音输入简单命令来模拟手术器械控制,包括输液泵、玻璃体切割器和透热疗法设备。该项目依赖于一个基于马尔可夫模型、特定说话者的商业孤立词识别器,并由作者创建和开发了特定的识别词汇表和应用软件。结果令人鼓舞。该系统在测试条件下表现良好,证明了其稳健性、易用性和准确性(平均单词识别率超过97%)。基于他们的经验,作者认为自动语音识别技术尽管存在一些局限性,如需要训练、依赖说话者以及词汇量相对较小,并且需要在操作条件下进行广泛测试,但仍值得进一步发展,并为新一代手术器械开辟了新的前景。

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