Issue No.02 - April-June (2013 vol.12)
Zhiwen Yu , Northwestern Polytechnical University
Xingshe Zhou , Northwestern Polytechnical University
Yuichi Nakamura , Kyoto University
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MPRV.2012.55
Extracting social semantics from multimodal meeting content can help meeting participants, organizers, and sponsors better understand the social dynamics of exchanging information. The authors present a framework for extracting both low-level (individual) and high-level (group) semantics.
Semantics, Human factors, Data mining, Feature extraction, Speech recognition, Support vector machines, Social factors,multimodal, Semantics, Human factors, Data mining, Feature extraction, Speech recognition, Support vector machines, Social factors, data mining, social semantics, human interaction, meeting
Zhiwen Yu, Xingshe Zhou, Yuichi Nakamura, "Extracting Social Semantics from Multimodal Meeting Content", IEEE Pervasive Computing, vol.12, no. 2, pp. 68-75, April-June 2013, doi:10.1109/MPRV.2012.55