Maurizio Mancini
Catherine Pelachaud
Skip Abstract Section
Skip Supplemental Material SectionAbstract
Laughter is a social signal capable of facilitating interaction in groups of people: it communicates interest, helps to improve creativity, and facilitates sociability. This article focuses on: endowing virtual characters with computational models of laughter synthesis, based on an expressivity-copying paradigm; evaluating how the physically co-presence of the laughing character impacts on the user’s perception of an audio stimulus and mood. We adopt music as a means to stimulate laughter. Results show that the character presence influences the user’s perception of music and mood. Expressivity-copying has an influence on the user’s perception of music, but does not have any significant impact on mood.
Supplemental Material
Available for Download
zip
mancini.zip (20.2 KB)
Supplemental movie, appendix, image and software files for, Implementing and Evaluating a Laughing Virtual Character
- V. Adelswärd. 1989. Laughter and dialogue: The social significance of laughter in institutional discourse. Nordic Journal of Linguistics 12, 02 (1989), 107--136.Google Scholar
Cross Ref
- J. N. Bailenson and N. Yee. 2005. Digital chameleons: Automatic assimilation of nonverbal gestures in immersive virtual environments. Psychological Science 16, 10 (2005), 814--819.Google ScholarCross Ref
- J. N. Bailenson, J. Blascovich, A. Beall, and J. M. Loomis. 2003. Interpersonal distance in immersive virtual environments. Personality and Social Psychology Bulletin 29, 7 (2003), 819--833.Google ScholarCross Ref
- R. Beale and C. Creed. 2009. Affective interaction: How emotional agents affect users. International Journal of Human-Computer Studies 67, 9 (2009), 755--776. Google ScholarDigital Library
- C. Becker-Asano and H. Ishiguro. 2009. Laughter in social robotics - no laughing matter. In Proceedings of the International Workshop on Social Intelligence Design. 287--300.Google Scholar
- C. Becker-Asano, T. Kanda, C. Ishi, and H. Ishiguro. 2009. How about laughter? Perceived naturalness of two laughing humanoid robots. In Proceedings of the 3rd International Conference on Affective Computing and Intelligent Interaction. IEEE, 1--6.Google Scholar
- P. Boersma and D. Weeninck. 2001. Praat, a system for doing phonetics by computer. Glot International 5, 9/10 (2001), 341--345.Google Scholar
- C. Broekema. 2011. Motion intensity matching in interaction with a virtual agent. In Proceedings of the 14th Twente Student Conference on IT.Google Scholar
- Antonio Camurri, Gualtiero Volpe, Stefano Piana, Maurizio Mancini, Radoslaw Niewiadomski, Nicola Ferrari, and Corrado Canepa. 2016. The dancer in the eye: Towards a multi-layered computational framework of qualities in movement. In Proceedings of the 3rd International Symposium on Movement and Computing (MOCO’16). ACM, New York, NY, Article 6, 7 pages. Google ScholarDigital Library
- G. Castellano, M. Mancini, C. Peters, and P. W. McOwan. 2012. Expressive copying behavior for social agents: A perceptual analysis. IEEE Transactions on Systems Man and Cybernetics-Part A-Systems and Humans 42, 3 (2012), 776. Google ScholarDigital Library
- A. Chapman. 1983. Humor and laughter in social interaction and some implications for humor research. In Handbook of Humor Research, Vol. 1, P. E. McGhee and J. H. Goldstein (Eds.). 135--157.Google ScholarCross Ref
- F. Charles, F. Pecune, G. Aranyi, C. Pelachaud, and M. Cavazza. 2015. ECA control using a single affective user dimension. In Proceedings of the 2015 ACM on International Conference on Multimodal Interaction. ACM, 183--190. Google ScholarDigital Library
- T. L. Chartrand and J. A. Bargh. 1994. The chameleon effect: The perception-behavior link and social interaction. Journal of Personality and Social Psychology 76 (1994), 893--910.Google ScholarCross Ref
- D. DeVault, R. Artstein, G. Benn, T. Dey, E. Fast, A. Gainer, K. Georgila, J. Gratch, A. Hartholt, M. Lhommet, and others. 2014. SimSensei kiosk: A virtual human interviewer for healthcare decision support. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 1061--1068. Google ScholarDigital Library
- Y. Ding, J. Huang, N. Fourati, T. Artières, and C. Pelachaud. 2014a. Upper body animation synthesis for a laughing character. In Intelligent Virtual Agents. Lecture Notes in Computer Science, Vol. 8637. 164--173.Google ScholarCross Ref
- Y. Ding and C. Pelachaud. 2015. Lip animation synthesis: A unified framework for speaking and laughing virtual agent. In Auditory-Visual Speech Processing (AVSP’15). 78--83.Google Scholar
- Y. Ding, K. Prepin, J. Huang, C. Pelachaud, and T. Artières. 2014b. Laughter animation synthesis. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems (AAMAS’14). 773--780. Google ScholarDigital Library
- R. I. M. Dunbar. 2008. Mind the gap: Or why humans are not just great apes. In Proceedings of the British Academy, Vol. 154.Google ScholarCross Ref
- D. P. French and S. Sutton. 2010. Reactivity of measurement in health psychology: How much of a problem is it? What can be done about it? British Journal of Health Psychology 15, 3 (2010), 453--468.Google ScholarCross Ref
- K. Grammer. 1990. Strangers meet: Laughter and nonverbal signs of interest in opposite-sex encounters. Journal of Nonverbal Behavior 14, 4 (1990), 209--236.Google ScholarCross Ref
- H. Griffin, M. Aung, B. Romera-Paredes, C. McLoughlin, G. McKeown, W. Curran, and N. Berthouze. 2015. Perception and automatic recognition of laughter from whole-body motion: Continuous and categorical perspectives. IEEE Transactions on Affective Computing PP, 99 (2015).Google Scholar
- J. Hofmann, T. Platt, W. Ruch, R. Niewiadomski, and J. Urbain. 2015. The influence of a virtual companion on amusement when watching funny films. Motivation and Emotion 39, 3 (2015), 434--447.Google ScholarCross Ref
- T. Huber and W. Ruch. 2007. Laughter as a uniform category? A historic analysis of different types of laughter. In Proceedings of the 10th Congress of the Swiss Society of Psychology.Google Scholar
- L. W. Hughes and J. B. Avey. 2009. Transforming with levity: Humor, leadership, and follower attitudes. Leadership 8 Organization Development Journal 30, 6 (2009), 540--562.Google Scholar
- D. Huron. 2004. Music-engendered laughter: An analysis of humor devices in PDQ Bach. In Proceedings of International Conference on Music Perception and Cognition. 700--704.Google Scholar
- Dana Kovarsky, Maura Curran, and Nicole Zobel Nichols. 2009. Laughter and communicative engagement in interaction. In Seminars in Speech and Language, Vol. 30. © Thieme Medical Publishers, 027--036.Google Scholar
- M. Lombard, T. B. Ditton, and L. Weinstein. 2009. Measuring presence: The temple presence inventory. In Proceedings of the 12th Annual International Workshop on Presence. 1--15.Google Scholar
- M. Mancini, G. Varni, D. Glowinski, and G. Volpe. 2012. Computing and evaluating the body laughter index. In Human Behavior Understanding, A. A. Salah, J. Ruiz-del Solar, C. Meriçli, and P.-Y. Oudeyer (Eds.). Lecture Notes in Computer Science, Vol. 7559. Springer, Berlin, 90--98. Google ScholarDigital Library
- V. Markaki, S. Merlino, L. Mondada, and F. Oloff. 2010. Laughter in professional meetings: The organization of an emergent ethnic joke. Journal of Pragmatics 42, 6 (2010), 1526--1542.Google ScholarCross Ref
- S. Marsella, J. Gratch, and P. Petta. 2010. Computational models of emotion. A Blueprint for Affective Computing—A Sourcebook and Manual. 21--46.Google Scholar
- W. S. McCulloch and W. Pitts. 1943. A logical calculus of the ideas immanent in nervous activity. The Bulletin of Mathematical Biophysics 5, 4 (1943), 115--133.Google ScholarCross Ref
- G. McKeown, W. Curran, C. McLoughlin, H. J. Griffin, and N. Bianchi-Berthouze. 2013. Laughter induction techniques suitable for generating motion capture data of laughter associated body movements. In Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on. IEEE, 1--5.Google Scholar
- C. Nagaoka, M. Komori, and S. Yoshikawa. 2007. Embodied Synchrony in Conversation. 331--351.Google Scholar
- R. Niewiadomski, J. Hofmann, J. Urbain, T. Platt, J. Wagner, B. Piot, H. Cakmak, S. Pammi, T. Baur, S. Dupont, and others. 2013. Laugh-aware virtual agent and its impact on user amusement. In Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems. 619--626. Google ScholarDigital Library
- M. J. Owren and J.-A. Bachorowski. 2003. Reconsidering the evolution of nonlinguistic communication: The case of laughter. Journal of Nonverbal Behavior 27 (2003), 183--200. Issue 3.Google ScholarCross Ref
- I. S. Pandzic and R. Forcheimer (Eds.). 2002. MPEG4 Facial Animation - The Standard, Implementations and Applications. John Wiley 8 Sons. Google ScholarDigital Library
- F. Pecune, A. Cafaro, M. Chollet, P. Philippe, and C. Pelachaud. 2014. Suggestions for extending SAIBA with the VIB platform. In Proceedings of the Workshop on Architectures and Standards for Intelligent Virtual Agents at IVA. 336--342.Google Scholar
- F. Pecune, M. Mancini, B. Biancardi, G. Varni, Y. Ding, C. Pelachaud, G. Volpe, and A. Camurri. 2015. Laughing with a virtual agent. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS’15). 1817--1818. Google ScholarDigital Library
- S. Piana, M. Mancini, A. Camurri, G. Varni, and G. Volpe. 2013. Automated analysis of non-verbal expressive gesture. In Human Aspects in Ambient Intelligence, T. Bosse, D. J. Cook, M. Neerincx, and F. Sadri (Eds.). Vol. 8. Atlantis Press, 41--54.Google Scholar
- T. Platt, J. Hofmann, W. Ruch, R. Niewiadomski, and J. Urbain. 2012. Experimental standards in research on AI and humor when considering psychology. In Proceedings of the AAAI Fall Symposium: Artificial Intelligence of Humor.Google Scholar
- R. Prada and A. Paiva. 2009. Teaming up humans with autonomous synthetic characters. Artificial Intelligence 173, 1 (2009), 80--103. Google ScholarDigital Library
- K. Prepin, M. Ochs, and C. Pelachaud. 2013. Beyond backchannels: Co-construction of dyadic stance by reciprocal reinforcement of smiles between virtual agents. In Proceedings of COGSCI 2013 the Annual Meeting of the Cognitive Science Society.Google Scholar
- R. R. Provine. 2001. Laughter: A Scientific Investigation. Penguin.Google Scholar
- W. Ruch and P. Ekman. 2001. The expressive pattern of laughter. In Emotion, Qualia and Consciousness, A. Kaszniak (Ed.). World Scientific Publishers, Tokyo, 426--443.Google Scholar
- W. Ruch and S. Rath. 1993. The nature of humor appreciation: Toward an integration of perception of stimulus properties and affective experience. Humor 6 (1993), 363--363.Google ScholarCross Ref
- J. Urbain, E. Bevacqua, T. Dutoit, A. Moinet, R. Niewiadomski, C. Pelachaud, B. Picart, J. Tilmanne, and J. Wagner. 2010. The AVLaughterCycle database. In Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC’10). 19--21.Google Scholar
- J. Urbain, H. Çakmak, and T. Dutoit. 2013. Automatic phonetic transcription of laughter and its application to laughter synthesis. In Proceedings of ACII. 153--158. Google ScholarDigital Library
- J. Urbain, R. Niewiadomski, J. Hofmann, E. Bantegnie, T. Baur, N. Berthouze, H. Cakmak, R. Cruz, S. Dupont, M. Geist, H. Griffin, F. Lingenfelser, M. Mancini, M. Miranda, G. Mckeown, S. Pammi, O. Pietquin, B. Piot, T. Platt, W. Ruch, A. Sharma, G. Volpe, and J. Wagner. 2012. Laugh machine. In Proceedings of the 8th International Summer Workshop on Multimodal Interfaces, eNTERFACE 12. 13--34.Google Scholar
- D. A. Winter. 1990. Biomechanics and Motor Control of Human Movement. John Wiley 8 Sons, Inc., Toronto.Google Scholar
- R. Zhao, A. Papangelis, and J. Cassell. 2014. Towards a dyadic computational model of rapport management for human-virtual agent interaction. In Intelligent Virtual Agents. Springer, 514--527.Google Scholar
Index Terms
- Implementing and Evaluating a Laughing Virtual Character
Recommendations
A Laughing Matter: Patterns of Laughter and the Effectiveness of Working Dyads
Poor communication in teams has been found to result in disappointing team performance. Integrating research on team communication and laughter, we tested hypotheses about the relationship between working dyads' patterns of laughter and their open ...
Model of the perception of smiling virtual character
AAMAS '12: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1A smile may convey different communicative intentions depending on subtle characteristics of the facial expression. Moreover, during an interaction, the expression of smile impacts on the observer's perception of both the social stance of the speaker ...
Rhythmic Body Movements of Laughter
ICMI '14: Proceedings of the 16th International Conference on Multimodal InteractionIn this paper we focus on three aspects of multimodal expressions of laughter. First, we propose a procedural method to synthesize rhythmic body movements of laughter based on spectral analysis of laughter episodes. For this purpose, we analyze laughter ...
Comments