A more comprehensive analysis of the cases where the system and the human disagreed on classification is reported in the conference presentation.
in this paper we present a multiple instance learning-based segmentation system that accurately labels 91.27% of the video frames of 500 continuous utterances (including 7 different subjects) from the publicly accessible NCSLGR corpus <http://secrets.rutgers.edu/dai/queryPages/> (Neidle and Vogler, 2012).