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Understanding and Predicting Bonding in Conversations Using Thin Slices of Facial Expressions and Body Language
Name
understanding-predicting-bonding-CameraReady.pdf
Description
Accepted version
Size
349.99 KB
Format
Adobe PDF
Checksum (MD5)
026425e33257f00ca1505b6627969293
Author(s)
Jaques, Natasha
McDuff, Daniel
Kim, Yoo Lim
Picard, Rosalind W.
Date Issued
2016
Publisher
Springer Nature America, Inc
Citation
Jaques, Natasha, McDuff, Daniel, Kim, Yoo Lim and Picard, Rosalind W. 2016. "Understanding and Predicting Bonding in Conversations Using Thin Slices of Facial Expressions and Body Language."
Version
Author's final manuscript
Abstract
© Springer International Publishing AG 2016. This paper investigates how an intelligent agent could be designed to both predict whether it is bonding with its user, and convey appropriate facial expression and body language responses to foster bonding. Video and Kinect recordings are collected from a series of naturalistic conversations, and a reliable measure of bonding is adapted and verified. A qualitative and quantitative analysis is conducted to determine the non-verbal cues that characterize both high and low bonding conversations. We then train a deep neural network classifier using one minute segments of facial expression and body language data, and show that it is able to accurately predict bonding in novel conversations.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://dx.doi.org/10.1007/978-3-319-47665-0_6
