arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2006.01916cs.HCcs.AIcs.LGeess.AS
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会话系统中韵律调制对用户参与度和满意度的影响

Quantifying the Effects of Prosody Modulation on User Engagement and Satisfaction in Conversational Systems

Emory University(埃默里大学)

Jason Ingyu Choi, Eugene Agichtein

摘要:

随着Alexa、Siri和Google Assistant等基于语音的助手变得无处不在,用户越来越希望与这些系统保持自然和信息丰富的对话。然而,对于一个开放域的会话系统是连贯的和引人入胜的,它必须能够保持用户的兴趣延长时间,而不会听起来无聊或烦人。在本文中,我们研究了一种自然的方法来解决这个问题,调制响应韵律,即,改变反应的音调和节奏,以表示高兴,悲伤或其他常见的情绪,以及使用预先录制的感叹词。直观地说,这种方法应该可以提高对话的自然性,但试图量化韵律调制对用户满意度和参与度的影响仍然具有挑战性。为了实现这一目标,我们报告了一项大规模实证研究的结果,该研究测量了韵律调制对多个会话域的用户行为和参与度的影响,无论是在每个回合之后,还是在整体会话水平上。我们的研究结果表明,韵律调制显着增加即时和整体用户满意度。然而,由于不同领域的影响各不相同,我们验证韵律调制不取代连贯的,信息丰富的内容的反应。总之,我们的研究结果提供了有用的工具和见解,以提高自然的反应在会话系统。

英文摘要:

As voice-based assistants such as Alexa, Siri, and Google Assistant become ubiquitous, users increasingly expect to maintain natural and informative conversations with such systems. However, for an open-domain conversational system to be coherent and engaging, it must be able to maintain the user's interest for extended periods, without sounding boring or annoying. In this paper, we investigate one natural approach to this problem, of modulating response prosody, i.e., changing the pitch and cadence of the response to indicate delight, sadness or other common emotions, as well as using pre-recorded interjections. Intuitively, this approach should improve the naturalness of the conversation, but attempts to quantify the effects of prosodic modulation on user satisfaction and engagement remain challenging. To accomplish this, we report results obtained from a large-scale empirical study that measures the effects of prosodic modulation on user behavior and engagement across multiple conversation domains, both immediately after each turn, and at the overall conversation level. Our results indicate that the prosody modulation significantly increases both immediate and overall user satisfaction. However, since the effects vary across different domains, we verify that prosody modulations do not substitute for coherent, informative content of the responses. Together, our results provide useful tools and insights for improving the naturalness of responses in conversational systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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