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[使用语音识别系统进行心脏病学的自动报告记录]

[Automatic report documentation in cardiology using a speech recognition system].

作者信息

Dietz U, Rupprecht H J, Espinola-Klein C, Meyer J

机构信息

II. Medizinische Klinik Johannes-Gutenberg-Universität, Mainz.

出版信息

Z Kardiol. 1996 Sep;85(9):684-8.

PMID:8992813
Abstract

Computer systems that can convert spoken text into written text have recently become available. In one such system, the phonetics of spoken words are compared with those of 32 000 stored words, with a statistical program helping to choose the word with the highest probability of being correct. We evaluated the practicability of the IBM Voice Type system for writing medical reports using a cardiologic vocabulary. A total of 200 medical documents were generated with a mean of 301 +/- 52 words. In the mean, 12 +/- 5 words were falsely recognized in each document, resulting in a rate of correct recognition of 95.1 +/- 2.5%. It is possible to correct a falsely recognized word by choosing an alternative word from a provided list, which worked in our case in 51% (6.1 +/- 2.8 words in each document). Correction of falsely recognized words had to be done by manual input 49% of the time (5.9 +/- 2.9 words in each document). The mean time demand for word correction amounted to 57 +/- 15 s for each document, whereas correction by manual input needed more time (37 +/- 14 s) than choosing from a list of alternative words (20 +/- 4s). A requirement for use of the Voice Type system is a reduced speech rate. Dictation of our documents took on average 260 s when done with a normal speech rate, and 400 s when done at a reduced speech rate. In conclusion, automatic writing of cardiologic reports can be done easily and with a low failure rate using the IBM Voice Type system with a cardiologic vocabulary. It takes about 3 min longer to create a medical text 1 1/2 pages long which is free of mistakes by using the Voice Type system than to simply dictate the text. Time can be saved by eliminating the need to check a preliminary report. The major advantage of automated reporting is that the written report is immediately available. For each discipline, specific vocabularies should be validated.

摘要

能够将语音文本转换为书面文本的计算机系统最近已投入使用。在这样一个系统中,会将口语单词的语音与32000个存储单词的语音进行比较,并有一个统计程序帮助选择最有可能正确的单词。我们使用心脏科词汇评估了IBM语音打字系统用于撰写医学报告的实用性。共生成了200份医学文档,平均每份文档有301±52个单词。平均而言,每份文档中有12±5个单词被错误识别,正确识别率为95.1±2.5%。可以通过从提供的列表中选择替代单词来纠正错误识别的单词,在我们的案例中,这种方法的成功率为51%(每份文档中有6.1±2.8个单词)。49%的情况下必须通过手动输入来纠正错误识别的单词(每份文档中有5.9±2.9个单词)。每份文档纠正错误识别单词的平均时间需求为57±15秒,而手动输入纠正所需时间(37±14秒)比从替代单词列表中选择要多(20±4秒)。使用语音打字系统的一个要求是降低语速。以正常语速听写我们的文档平均需要260秒,以降低语速听写则需要400秒。总之,使用具有心脏科词汇的IBM语音打字系统可以轻松地进行心脏科报告的自动撰写,且错误率较低。使用语音打字系统创建一份1.5页长且无错误的医学文本比简单听写文本大约要多花3分钟。通过无需检查初步报告可以节省时间。自动报告的主要优点是书面报告立即可用。对于每个学科,应验证特定的词汇。

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