Abstract
More and more companies are putting emphasis on communication skill in the recruitment of their employees and adopt group discussion as part of their recruitment interview. In our ongoing project, we aim to develop a training system that can provide advices to its users in improving the perception of their communication skill during group discussion. In order to realize this goal, a conceptual unit of communicational behaviors and a template of communication style are required. We propose the use of functional roles of the participants in group discussions as this unit. In order to incorporate the use of functional roles for improving the perception of participants’ communication skill, the first task is automatic detection of the participants’ functional roles in real-time. We previously proposed a SVM based model for this task but the results were only moderate. We expect including temporal characteristics, frame-wise interaction of modalities, and inter-person interaction can improve the classification accuracy and explored the use of RNN based networks to see the effectiveness of these factors.
Keywords
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Aran, O., Gatica-Perez, D.: One of a kind: inferring personality impressions in meetings. In: Proceedings of 15th ACM International Conference on Multimodal Interaction (ICMI 2013), Sydney, Australia, December 2013
Argyle, M., Cook, M.: Gaze and Mutual Gaze. Cambridge University Press, Cambridge (1976)
Bengio, Y., Glorot, X., Bordes, A.: Deep sparse rectifier neural networks. In: Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS), vol. 15, pp. 315–323 (2011)
Benne, K.D., Sheats, P.: Functional roles of group members. J. Soc. Issues 4(2), 41–49 (1948)
Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321–357 (2002)
Clark, H.H., Carlson, T.B.: Hearers and speech acts. Language 58(2), 332–373 (1982)
Ekman, P., Friesen, W.V., Hager, J.C.: Facial Action Coding System (FACS). Website (2002). http://www.face-and-emotion.com/dataface/facs/description.jsp
Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)
Hall, J.A., Coats, E.J., LeBeau, L.S.: Nonverbal behavior and the vertical dimension of social relations: a meta-analysis. Psychol. Bull. 131(6), 898–924 (2005)
Hare, P.: Types of roles in small groups, a bit history and a current perspective. Small Group Res. 25(3), 433–448 (1994)
Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735–1780 (1997)
Huang, H.H., Zhang, Q., Okada, S., Kuwabara, K., Nishida, T.: Adopting functional roles for improving participants’ communication skill in group discussion conversation. In: Workshop on Group Interaction Frontiers in Technology (GIFT 2018), 20th ACM International Conference on Multimodal Interaction (ICMI 2018), Boulder, USA, October 2018
Institute, H.R.: Report of the 2017 investigation on the trend in the recruitment of new graduates (2017). (in Japanese)
Keidanren Japan Business Federation: Reports of the 2017 investigation on the recruitment of new graduates, November 2017. (in Japanese)
Kendon, A.: Some functions of gaze direction in social interaction. Acta Psychol. 26, 22–63 (1967)
Lausberg, H., Sloetjes, H.: Coding gestural behavior with the NEUROGES-ELAN system. Behav. Res. Methods 41(3), 841–849 (2009)
McNeill, D.: Hand and Mind. The University of Chicago Press, Chicago (1992)
Muralidhar, S., Nguyen, L.S., Frauendorfer, D., Odobez, J.M., Mast, M.S., Gatica-Perez, D.: Training on the job: behavioral analysis of job interviews in hospitality. In: 18th ACM International Conference on Multimodal Interaction (ICMI 2016), Tokyo, Japan, pp. 84–91, November 2016
Nihei, F., Nakano, Y.I., Hayashi, Y., Huang, H.H., Okada, S.: Predicting influential statements in group discussions using speech and head motion information. In: 16th International Conference on Multimodal Interaction (ICMI 2014), Istanbul, pp. 136–143, November 2014
Okada, S., Nakano, Y., Hayashi, Y., Takase, Y., Nitta, K.: Estimating communication skills using dialogue acts and nonverbal features in multiple discussion datasets. In: 18th ACM International Conference on Multimodal Interaction (ICMI 2016), Tokyo, pp. 169–176, November 2016
Raducanu, B., Vitria, J., Gatica-Perez, D.: You are fired! Nonverbal role analysis in competitive meetings. In: 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009), Taipei, Taiwan, April 2009
Schiavo, G., Cappelletti, A., Mencarini, E., Stock, O., Zancanaro, M.: Overt or subtle? Supporting group conversations with automatically targeted directives. In: Proceedings of the 19th International Conference on Intelligent User Interfaces (IUI 2014), pp. 225–234 (2014)
Schuller, B., Steidl, S., Batliner, A.: The interspeech 2009 emotion challenge. In: 10th Annual Conference of the International Speech Communication Association (Interspeech 2009), Brighton, United Kingdom, September 2009
Zancanaro, M., Lepri, B., Pianesi, F.: Automatic detection of group functional roles in face to face interactions. In: Proceedings of the 8th International Conference on Multimodal Interfaces (ICMI 2006), pp. 28–34 (2006)
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This research is partially supported by KAKENHI: Grant-in-Aid for Scientific Research (A), Grant No. 19H01120.
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Huang, HH., Nishida, T. (2020). Investigation on the Fusion of Multi-modal and Multi-person Features in RNNs for Detecting the Functional Roles of Group Discussion Participants. In: Meiselwitz, G. (eds) Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. HCII 2020. Lecture Notes in Computer Science(), vol 12194. Springer, Cham. https://doi.org/10.1007/978-3-030-49570-1_34
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