Automatic discrimination of laughter using distributed sEMG

Sarah Cosentino, S. Sessa, W. Kong, Di Zhang, Atsuo Takanishi, N. Bianchi-Berthouze

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Laughter is a very interesting non-verbal human vocalization. It is classified as a semi voluntary behavior despite being a direct form of social interaction, and can be elicited by a variety of very different stimuli, both cognitive and physical. Automatic laughter detection, analysis and classification will boost progress in affective computing, leading to the development of more natural human-machine communication interfaces. Surface Electromyography (sEMG) on abdominal muscles or invasive EMG on the larynx show potential in this direction, but these kinds of EMG-based sensing systems cannot be used in ecological settings due to their size, lack of reusability and uncomfortable setup. For this reason, they cannot be easily used for natural detection and measurement of a volatile social behavior like laughter in a variety of different situations. We propose the use of miniaturized, wireless, dry-electrode sEMG sensors on the neck for the detection and analysis of laughter. Even if with this solution the activation of specific larynx muscles cannot be precisely measured, it is possible to detect different EMG patterns related to larynx function. In addition, integrating sEMG analysis on a multisensory compact system positioned on the neck would improve the overall robustness of the whole sensing system, enabling the synchronized measure of different characteristics of laughter, like vocal production, head movement or facial expression; being at the same time less intrusive, as the neck is normally more accessible than abdominal muscles. In this paper, we report laughter discrimination rate obtained with our system depending on different conditions.

Original languageEnglish
Title of host publication2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages691-697
Number of pages7
ISBN (Electronic)9781479999538
DOIs
Publication statusPublished - 2015 Dec 2
Event2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015 - Xi'an, China
Duration: 2015 Sep 212015 Sep 24

Other

Other2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015
CountryChina
CityXi'an
Period15/9/2115/9/24

    Fingerprint

Keywords

  • affective computing
  • electromyography
  • EMG
  • laughter
  • laughter computing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software

Cite this

Cosentino, S., Sessa, S., Kong, W., Zhang, D., Takanishi, A., & Bianchi-Berthouze, N. (2015). Automatic discrimination of laughter using distributed sEMG. In 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015 (pp. 691-697). [7344644] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACII.2015.7344644