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首页> 外文会议>Annual CHI Conferenceon Human Factors in Computing Systems >Augmenting Social Interactions: Realtime Behavioural Feedback using Social Signal Processing Techniques
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Augmenting Social Interactions: Realtime Behavioural Feedback using Social Signal Processing Techniques

机译：增强社交互动：使用社交信号处理技术实时行为反馈

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摘要

Nonverbal and unconscious behaviour is an important component of daily human-human interaction. This is especially true in situations such as public speaking, job interviews or information sensitive conversations, where researchers have shown that an increased awareness of one's behaviour can improve the outcome of the interaction. With wearable technology, such as Google Glass, we now have the opportunity to augment social interactions and provide realtime feedback on one's behaviour in an unobtrusive way. In this paper we present Logue, a system that provides realtime feedback on the presenters' openness, body energy and speech rate during public speaking. The system analyses the user's nonverbal behaviour using social signal processing techniques and gives visual feedback on a head-mounted display. We conducted two user studies with a staged and a real presentation scenario which yielded that Logue's feedback was perceived helpful and had a positive impact on the speaker's performance.
机译：非言语和无意识的行为是日常人类互动的重要组成部分。在公开讲话，求职或信息敏感的谈话中尤其如此，研究人员表明，提高对一个人的行为的认识可以改善互动的结果。具有可穿戴技术，例如Google Glass，我们现在有机会增加社交互动，并以不引人注目的方式提供对一个人行为的实时反馈。在本文中，我们呈现了在公开演讲期间为演示者开放，身体能量和语音率提供实时反馈的系统。系统使用社交信号处理技术分析用户的非语言行为，并在头戴式显示器上提供视觉反馈。我们用阶段和真正的演示方案进行了两个用户研究，从而产生了日志的反馈让人有用，对演讲者的表现产生积极影响。

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