MACH: My Automated Conversation coacH
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Picard_MACH.pdf
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1.2 MB
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Author(s)
Courgeon, Matthieu
Martin, Jean-Claude
Mutlu, Bilge
Picard, Rosalind W.
Hoque, Mohammed Ehasanul
Date Issued
September 2013
Journal
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (UbiComp '13)
Publisher
Association for Computing Machinery (ACM)
Citation
Mohammed (Ehsan) Hoque, Matthieu Courgeon, Jean-Claude Martin, Bilge Mutlu, and Rosalind W. Picard. 2013. MACH: my automated conversation coach. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (UbiComp '13). ACM, New York, NY, USA, 697-706.
Version
Author's final manuscript
Abstract
MACH--My Automated Conversation coacH--is a novel system that provides ubiquitous access to social skills training. The system includes a virtual agent that reads facial expressions, speech, and prosody and responds with verbal and nonverbal behaviors in real time. This paper presents an application of MACH in the context of training for job interviews. During the training, MACH asks interview questions, automatically mimics certain behavior issued by the user, and exhibit appropriate nonverbal behaviors. Following the interaction, MACH provides visual feedback on the user's performance. The development of this application draws on data from 28 interview sessions, involving employment-seeking students and career counselors. The effectiveness of MACH was assessed through a weeklong trial with 90 MIT undergraduates. Students who interacted with MACH were rated by human experts to have improved in overall interview performance, while the ratings of students in control groups did not improve. Post-experiment interviews indicate that participants found the interview experience informative about their behaviors and expressed interest in using MACH in the future.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2493432.2493502
