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.
翻译:多数在线信息来源都以文字为基础,以英语等西方语言提供。然而,许多新的和第一次的互联网用户在英语熟练程度低的情况下,无法在网上获取重要信息。一些研究人员侧重于为这一人口群体建立对话信息系统,并强调了建立对信息来源的信任的重要性。在这项工作中,我们在谷歌助理平台上开发了四种基于语音的聊天机版本,我们在这个平台上对机器人的性别、友好和个性进行差异。我们发现,用户将女性版本的机器人排位定得比其他版本更加个性化;然而,当对机器人进行单独评分时,其评级取决于机器人是否有能力理解用户的口头询问并做出准确回应。