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语音识别对消费者数字健康任务中问题解决和记忆的影响:对照实验室实验

Effect of Speech Recognition on Problem Solving and Recall in Consumer Digital Health Tasks: Controlled Laboratory Experiment.

作者信息

Chen Jessica, Lyell David, Laranjo Liliana, Magrabi Farah

机构信息

Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, North Ryde, Australia.

出版信息

J Med Internet Res. 2020 Jun 1;22(6):e14827. doi: 10.2196/14827.

Abstract

BACKGROUND

Recent advances in natural language processing and artificial intelligence have led to widespread adoption of speech recognition technologies. In consumer health applications, speech recognition is usually applied to support interactions with conversational agents for data collection, decision support, and patient monitoring. However, little is known about the use of speech recognition in consumer health applications and few studies have evaluated the efficacy of conversational agents in the hands of consumers. In other consumer-facing tools, cognitive load has been observed to be an important factor affecting the use of speech recognition technologies in tasks involving problem solving and recall. Users find it more difficult to think and speak at the same time when compared to typing, pointing, and clicking. However, the effects of speech recognition on cognitive load when performing health tasks has not yet been explored.

OBJECTIVE

The aim of this study was to evaluate the use of speech recognition for documentation in consumer digital health tasks involving problem solving and recall.

METHODS

Fifty university staff and students were recruited to undertake four documentation tasks with a simulated conversational agent in a computer laboratory. The tasks varied in complexity determined by the amount of problem solving and recall required (simple and complex) and the input modality (speech recognition vs keyboard and mouse). Cognitive load, task completion time, error rate, and usability were measured.

RESULTS

Compared to using a keyboard and mouse, speech recognition significantly increased the cognitive load for complex tasks (Z=-4.08, P<.001) and simple tasks (Z=-2.24, P=.03). Complex tasks took significantly longer to complete (Z=-2.52, P=.01) and speech recognition was found to be overall less usable than a keyboard and mouse (Z=-3.30, P=.001). However, there was no effect on errors.

CONCLUSIONS

Use of a keyboard and mouse was preferable to speech recognition for complex tasks involving problem solving and recall. Further studies using a broader variety of consumer digital health tasks of varying complexity are needed to investigate the contexts in which use of speech recognition is most appropriate. The effects of cognitive load on task performance and its significance also need to be investigated.

摘要

背景

自然语言处理和人工智能的最新进展促使语音识别技术得到广泛应用。在消费者健康应用中,语音识别通常用于支持与对话代理的交互,以进行数据收集、决策支持和患者监测。然而,对于语音识别在消费者健康应用中的使用情况知之甚少,并且很少有研究评估消费者使用对话代理的效果。在其他面向消费者的工具中,认知负荷被认为是影响语音识别技术在涉及问题解决和回忆的任务中使用的一个重要因素。与打字、点击相比,用户发现同时思考和说话更加困难。然而,语音识别对执行健康任务时认知负荷的影响尚未得到探索。

目的

本研究旨在评估语音识别在涉及问题解决和回忆的消费者数字健康任务中的文档记录使用情况。

方法

招募了50名大学教职员工和学生,在计算机实验室中使用模拟对话代理进行四项文档记录任务。任务的复杂性因所需的问题解决和回忆量(简单和复杂)以及输入方式(语音识别与键盘和鼠标)而异。测量了认知负荷、任务完成时间、错误率和可用性。

结果

与使用键盘和鼠标相比,语音识别显著增加了复杂任务(Z = -4.08,P <.001)和简单任务(Z = -2.24,P =.03)的认知负荷。复杂任务完成时间显著更长(Z = -2.52,P =.01),并且发现语音识别总体上比键盘和鼠标的可用性更低(Z = -3.30,P =.001)。然而,对错误没有影响。

结论

对于涉及问题解决和回忆的复杂任务,使用键盘和鼠标比语音识别更可取。需要使用更广泛的各种不同复杂程度的消费者数字健康任务进行进一步研究,以调查语音识别最适合使用的背景。还需要研究认知负荷对任务绩效的影响及其重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6a3/7296411/89f91020bfc6/jmir_v22i6e14827_fig1.jpg

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