DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Youngki | - |
dc.contributor.author | Min, Chulhong | - |
dc.contributor.author | Hwang, Chanyou | - |
dc.contributor.author | Lee, Jaeung | - |
dc.contributor.author | HWANG, INSEOK | - |
dc.contributor.author | Ju, Younghyun | - |
dc.contributor.author | Yoo, Chungkuk | - |
dc.contributor.author | Moon, Miri | - |
dc.contributor.author | Lee, Uichin | - |
dc.contributor.author | Song, Junehwa | - |
dc.date.accessioned | 2020-11-25T04:51:33Z | - |
dc.date.available | 2020-11-25T04:51:33Z | - |
dc.date.created | 2020-11-15 | - |
dc.date.issued | 2013-06-28 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/104352 | - |
dc.description.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. | - |
dc.language | English | - |
dc.publisher | ACM | - |
dc.relation.isPartOf | MobiSys 2013 (11th ACM International Conference on Mobile Systems, Applications, and Services) | - |
dc.relation.isPartOf | Proceedings of the 11th ACM International Conference on Mobile Systems, Applications, and Services | - |
dc.title | SocioPhone: everyday face-to-face interaction monitoring platform using multi-phone sensor fusion | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.identifier.bibliographicCitation | MobiSys 2013 (11th ACM International Conference on Mobile Systems, Applications, and Services), pp.375 - 388 | - |
dc.citation.conferenceDate | 2013-06-25 | - |
dc.citation.conferencePlace | CH | - |
dc.citation.endPage | 388 | - |
dc.citation.startPage | 375 | - |
dc.citation.title | MobiSys 2013 (11th ACM International Conference on Mobile Systems, Applications, and Services) | - |
dc.contributor.affiliatedAuthor | HWANG, INSEOK | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
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