Note: Evaluating Trust in the Context of Conversational Information Systems for new users of the Internet

Anurag Aribandi, Divyanshu Agrawal, D. Chakraborty
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Abstract

Most online information sources are text-based and in Western Languages like English. However, many new and first time users of the Internet are in contexts with low English proficiency and are unable to access vital information online. Several researchers have focused on building conversational information systems over voice for this demographic, and also highlighted the importance of building trust towards the information source. In this work we develop four versions of a voice based chat-bot on the Google Assistant platform in which we vary the gender, friendliness and personalisation of the bot. We find that the users rank the female version of the bot with more personalisations over the others; however when rating the bots individually, the ratings depend on the ability of the bot to understand the users’ spoken query and respond accurately.
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注:评估互联网新用户在对话信息系统背景下的信任
大多数在线信息源都是基于文本的,并且使用英语等西方语言。然而,许多互联网的新用户和第一次用户都处于英语水平较低的环境中,无法在网上获取重要信息。一些研究人员专注于为这一人群建立语音对话信息系统,并强调了对信息源建立信任的重要性。在这项工作中,我们在谷歌助理平台上开发了四个版本的基于语音的聊天机器人,其中我们改变了机器人的性别,友好度和个性化。我们发现,用户认为女性版本的机器人比其他版本更个性化;然而,当对机器人进行单独评级时,评级取决于机器人理解用户语音查询和准确响应的能力。
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