会话代理的启发式评价

Raina Langevin, Ross J. Lordon, T. Avrahami, Benjamin R. Cowan, Tad Hirsch, Gary Hsieh
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引用次数: 45

摘要

随着企业和用户采用一系列对话代理,包括聊天机器人和语音助手,对话界面越来越受欢迎。虽然已经提出了指导方针,但还没有一套可用性启发式来指导和评估会话代理设计。在本文中,我们提出了一套基于专家反馈的尼尔森启发式的会话代理启发式。然后,我们通过参与者在两个会话代理,一个聊天机器人和一个基于语音的个人助理上进行的两轮评估来验证启发式。我们发现,当使用我们的启发式方法来评估两个界面时,评估者能够识别出比使用尼尔森启发式方法更多的可用性问题。我们建议我们的启发式方法成功地识别与对话内容、交互设计、帮助和指导、类人特征和数据隐私相关的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heuristic Evaluation of Conversational Agents
Conversational interfaces have risen in popularity as businesses and users adopt a range of conversational agents, including chatbots and voice assistants. Although guidelines have been proposed, there is not yet an established set of usability heuristics to guide and evaluate conversational agent design. In this paper, we propose a set of heuristics for conversational agents adapted from Nielsen’s heuristics and based on expert feedback. We then validate the heuristics through two rounds of evaluations conducted by participants on two conversational agents, one chatbot and one voice-based personal assistant. We find that, when using our heuristics to evaluate both interfaces, evaluators were able to identify more usability issues than when using Nielsen’s heuristics. We propose that our heuristics successfully identify issues related to dialogue content, interaction design, help and guidance, human-like characteristics, and data privacy.
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