Visual Prosody: Facial Movements Accompanying Speech
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Automatic Analysis of Multimodal Group Actions in Meetings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting information from multimedia meeting collections
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Automatic detection of group functional roles in face to face interactions
Proceedings of the 8th international conference on Multimodal interfaces
Detection and application of influence rankings in small group meetings
Proceedings of the 8th international conference on Multimodal interfaces
Proceedings of the 9th international conference on Multimodal interfaces
Using the influence model to recognize functional roles in meetings
Proceedings of the 9th international conference on Multimodal interfaces
Honest Signals: How They Shape Our World
Honest Signals: How They Shape Our World
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
You are fired! Nonverbal role analysis in competitive meetings
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Automatic nonverbal analysis of social interaction in small groups: A review
Image and Vision Computing
Modeling dominance in group conversations using nonverbal activity cues
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on multimodal processing in speech-based interactions
IEEE Transactions on Multimedia
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This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of "The Apprentice" reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority.