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| Content Provider | ACM Digital Library |
|---|---|
| Author | Yoo, Chungkuk Lee, Youngki Hwang, Inseok Lee, Jaeung Lee, Uichin Min, Chulhong Hwang, Chanyou Moon, Miri Ju, Younghyun Song, Junehwa |
| Abstract | In this paper, we propose SocioPhone, a novel initiative to build a mobile platform for face-to-face interaction monitoring. Face-to-face interaction, especially conversation, is a fundamental part of everyday life. Interaction-aware applications aimed at facilitating group conversations have been proposed, but have not proliferated yet. Useful contexts to capture and support face-to-face interactions need to be explored more deeply. More important, recognizing delicate conversational contexts with commodity mobile devices requires solving a number of technical challenges. As a first step to address such challenges, we identify useful meta-linguistic contexts of conversation, such as turn-takings, prosodic features, a dominant participant, and pace. These serve as cornerstones for building a variety of interaction-aware applications. SocioPhone abstracts such useful meta-linguistic contexts as a set of intuitive APIs. Its runtime efficiently monitors registered contexts during in-progress conversations and notifies applications on-the-fly. Importantly, we have noticed that online turn monitoring is the basic building block for extracting diverse meta-linguistic contexts, and have devised a novel volume-topography-based method. We show the usefulness of SocioPhone with several interesting applications: SocioTherapist, SocioDigest, and Tug-of-War. Also, we show that our turn-monitoring technique is highly accurate and energy-efficient under diverse real-life situations. |
| Starting Page | 375 |
| Ending Page | 388 |
| Page Count | 14 |
| File Format | |
| ISBN | 9781450316729 |
| DOI | 10.1145/2462456.2465426 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-06-26 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Social Face-to-face Platform Interaction Conversation Mobile Volume topography |
| Content Type | Text |
| Resource Type | Article |
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