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How productivity improves in hands-free continuous dictation tasks: lessons learned from a longitudinal study

机译:如何在免提连续听写任务中提高生产率:从纵向研究中学到的经验教训

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Speech recognition technology continues to improve, but users still experience significant difficulty using the software to create and edit documents. The reported composition speed using speech software is only between 8 and 15 words per minute [Proc CHI 99 (1999) 568; Universal Access Inform Soc 1 (2001) 4], much lower than people's normal speaking speed of 125-150 words per minute. What causes the huge gap between natural speaking and composing using speech recognition? Is it possible to narrow the gap and make speech recognition more promising to users? In this paper we discuss users' learning processes and the difficulties they experience as related to continuous dictation tasks using state of the art Automatic Speech Recognition (ASR) software. Detailed data was collected for the first time on various aspects of the three activities involved in document composition tasks: dictation, navigation, and correction. The results indicate that navigation and error correction accounted for big chunk of the dictation task during the early stages of interaction. As users gained more experience, they became more efficient at dictation, navigation and error correction. However, the major improvements in productivity were due to dictation quality and the usage of navigation commands. These results provide insights regarding the factors that cause the gap between user expectation with speech recognition software and the reality of use, and how those factors changed with experience. Specific advice is given to researchers as to the most critical issues that must be addressed.
机译:语音识别技术不断改进,但是用户在使用该软件创建和编辑文档时仍然遇到很大困难。据报道,使用语音软件的合成速度仅为每分钟8至15个单词[Proc CHI 99(1999)568; Universal Access Inform Soc 1(2001)4],远低于人们正常的说话速度,即每分钟125-150个单词。是什么导致自然说话和使用语音识别作曲之间的巨大差距?是否可以缩小差距并使语音识别对用户更有希望?在本文中,我们使用最先进的自动语音识别(ASR)软件讨论用户的学习过程以及与连续听写任务相关的困难。首次收集了有关文档撰写任务涉及的三个活动的各个方面的详细数据:听写,导航和更正。结果表明,在交互的早期阶段,导航和错误纠正占了命令任务的很大一部分。随着用户获得更多的经验,他们在听写,导航和错误纠正方面变得更加高效。但是,生产力的主要提高是由于命令质量和导航命令的使用。这些结果提供了有关导致语音识别软件的用户期望与实际使用之间造成差距的因素的见解,以及这些因素如何随体验而变化。针对必须解决的最关键问题,向研究人员提供了具体建议。

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