Paper Info
Title
Predicting Influential Statements in Group Discussions using Speech and Head Motion Information
Abstract
Group discussions are used widely when generating new ideas and forming decisions as a group. Therefore, it is assumed that giving social influence to other members through facilitating the discussion is an important part of discussion skill. This study focuses on influential statements that affect discussion flow and highly related to facilitation, and aims to establish a model that predicts influential statements in group discussions. First, we collected a multimodal corpus using different group discussion tasks; in-basket and case-study. Based on schemes for analyzing arguments, each utterance was annotated as being influential or not. Then, we created classification models for predicting influential utterances using prosodic features as well as attention and head motion information from the speaker and other members of the group. In our model evaluation, we discovered that the assessment of each participant in terms of discussion facilitation skills by experienced observers correlated highly to the number of influential utterances by a given participant. This suggests that the proposed model can predict influential statements with considerable accuracy, and the prediction results can be a good predictor of facilitators in group discussions.
Year
DOI
Venue
2014
10.1145/2663204.2663248
ICMI
Keywords
Field
DocType
facilitation,nonverbal information,influential statements,group discussion,synchronous interaction
Group discussion,Facilitation,Computer science,Utterance,Cognitive psychology,Social influence,Human–computer interaction,Artificial intelligence
Conference
Citations 
PageRank 
References 
14
0.72
20
Authors
5
Name
Order
Citations
PageRank
Fumio Nihei1184.52
Yukiko Nakano250162.37
Yuki Hayashi33811.12
Hung-Hsuan Huang414032.60
Shogo Okada510120.10