Laugh When You’re Winning

1. Bachorowski, J., Smoski, M.J., Owren, M.J.: Automatic discrimination between laughter and speech. Journal of the Acoustical Society of America 110, 1581–1597 (2001)

   Article  Google Scholar 

2. Becker-Asano, C., Ishiguro, H.: Laughter in social robotics - no laughing matter. In: International Workshop on Social Intelligence Design (SID 2009), pp. 287–300 (2009)

   Google Scholar 

3. Becker-Asano, C., Kanda, T., Ishi, C., Ishiguro, H.: How about laughter? perceived naturalness of two laughing humanoid robots. In: 3rd International Conference on Affective Computing & Intelligent Interaction, Affective Computing and Intelligent Interaction and Workshops, pp. 1–6 (2009)

   Google Scholar 

4. Bernhardt, D., Robinson, P.: Detecting affect from non-stylised body motions. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds.) ACII 2007. LNCS, vol. 4738, pp. 59–70. Springer, Heidelberg (2007)

   Chapter  Google Scholar 

5. Bourgeois, P., Hess, U.: The impact of social context on mimicry. Biological Psychology 77(3), 343–352 (2008)

   Article  Google Scholar 

6. Brand, M.: Voice puppetry. In: Proceedings of Conference on Computer Graphics and Interactive Techniques, pp. 21–28 (1999)

   Google Scholar 

7. Bregler, C., Covell, M., Slaney, M.: Video rewrite: Driving visual speech with audio. In: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1997, pp. 353–360. ACM Press/Addison-Wesley Publishing Co., New York (1997), http://dx.org/10.1145/258734.258880

   Chapter  Google Scholar 

8. Cai, R., Lu, L., Zhang, H., Cai, L.: Highlight sound effects detection in audio stream. In: Proceedings of the 2003 IEEE International Conference on Multimedia and Expo (ICME). Baltimore, USA, pp. 37–40 (2003)

   Google Scholar 

9. Castellano, G., Villalba, S.D., Camurri, A.: Recognising human emotions from body movement and gesture dynamics. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds.) ACII 2007. LNCS, vol. 4738, pp. 71–82. Springer, Heidelberg (2007)

   Chapter  Google Scholar 

10. Cohen, M.M., Massaro, D.W.: Modeling coarticulation in synthetic visual speech. In: Models and Techniques in Computer Animation, pp. 139–156. Springer (1993)

    Google Scholar 

11. Cosker, D., Edge, J.: Laughing, crying, sneezing and yawning: Automatic voice driven animation of non-speech articulations. In: Proceedings of Computer Animation and Social Agents (CASA 2009), pp. 21–24 (2009)

    Google Scholar 

12. Deng, Z., Lewis, J., Neumann, U.: Synthesizing speech animation by learning compact speech co-articulation models. In: Computer Graphics International 2005, pp. 19–25 (2005)

    Google Scholar 

13. DiLorenzo, P.C., Zordan, V.B., Sanders, B.L.: Laughing out loud: Control for modeling anatomically inspired laughter using audio. ACM Transactions on Graphics (TOG) 27(5), 125 (2008)

    Article  Google Scholar 

14. Ezzat, T., Geiger, G., Poggio, T.: Trainable videorealistic speech animation. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 57–64 (2004)

    Google Scholar 

15. Fukushima, S., Hashimoto, Y., Nozawa, T., Kajimoto, H.: Laugh enhancer using laugh track synchronized with the user’s laugh motion. In: CHI 2010 Extended Abstracts on Human Factors in Computing Systems, CHI EA 2010, pp. 3613–3618. ACM, New York (2010)

    Google Scholar 

16. Gilroy, S.W., Cavazza, M., Niranen, M., Andre, E., Vogt, T., Urbain, J., Benayoun, M., Seichter, H., Billinghurst, M.: Pad-based multimodal affective fusion. In: 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009 (2009)

    Google Scholar 

17. Gosling, S., Rentfrow, P.J., Swann, W.B.: A very brief measure of the big-five personality domains. Journal of Research in Personality 37(6), 504–528 (2003)

    Article  Google Scholar 

18. Hofmann, J., Platt, T., Urbain, J., Niewiadomski, R., Ruch, W.: Laughing avatar interaction evaluation form. Unpublished Research Instrument (2012)

    Google Scholar 

19. Kennedy, L., Ellis, D.: Laughter detection in meetings. In: NIST ICASSP 2004 Meeting Recognition Workshop, pp. 118–121. Montreal (May 2004)

    Google Scholar 

20. Kleinsmith, A., Bianchi-Berthouze, N.: Affective body expression perception and recognition: A survey (2012)

    Google Scholar 

21. Kleinsmith, A., Bianchi-Berthouze, N., Steed, A.: Automatic recognition of non-acted affective postures. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(4), 1027–1038 (2011)

    Article  Google Scholar 

22. Knox, M.T., Mirghafori, N.: Automatic laughter detection using neural networks. In: Proceedings of Interspeech 2007, pp. 2973–2976. Antwerp, Belgium (2007)

    Google Scholar 

23. Kshirsagar, S., Magnenat-Thalmann, N.: Visyllable based speech animation. Comput. Graph. Forum 22(3), 632–640 (2003)

    Article  Google Scholar 

24. Lasarcyk, E., Trouvain, J.: Imitating conversational laughter with an articulatory speech synthesis. In: Proceedings of the Interdisciplinary Workshop on The Phonetics of Laughter, pp. 43–48 (2007)

    Google Scholar 

25. Leite, I., Castellano, G., Pereira, A., Martinho, C., Paiva, A.: Modelling empathic behaviour in a robotic game companion for children: An ethnographic study in real-world settings. In: Proceedings of the Seventh Annual ACM/IEEE International Conference on Human-Robot Interaction, pp. 367–374. ACM (2012)

    Google Scholar 

26. Liu, W., Yin, B., Jia, X., Kong, D.: Audio to visual signal mappings with hmm. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2004 (2004)

    Google Scholar 

27. Mancini, M., Glowinski, D., Massari, A.: Realtime expressive movement detection using the eyesweb xmi platform. In: Camurri, A., Costa, C. (eds.) INTETAIN. LNICST, vol. 78, pp. 221–222. Springer (2011)

    Google Scholar 

28. Mancini, M., Hofmann, J., Platt, T., Volpe, G., Varni, G., Glowinski, D., Ruch, W., Camurri, A.: Towards automated full body detection of laughter driven by human expert annotation. In: Proceedings of the Fifth Biannual Humaine Association Conference on Affective Computing and Intelligent Interaction, Affective Interaction in Natural Environments (AFFINE) Workshop, Geneva, Switzerland, pp. 757–762 (2013)

    Google Scholar 

29. Mancini, M., Varni, G., Glowinski, D., Volpe, G.: Computing and evaluating the body laughter index. Human Behavior Understanding, 90–98 (2012)

    Google Scholar 

30. Meng, H., Kleinsmith, A., Bianchi-Berthouze, N.: Multi-score learning for affect recognition: The case of body postures. In: D’Mello, S., Graesser, A., Schuller, B., Martin, J.-C. (eds.) ACII 2011, Part I. LNCS, vol. 6974, pp. 225–234. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

31. Niewiadomski, R., Mancini, M., Baur, T., Varni, G., Griffin, H., Aung, M.: MMLI: Multimodal multiperson corpus of laughter in interaction. In: Fourth Int. Workshop on Human Behavior Understanding, in Conjunction with ACM Multimedia 2013 (2013)

    Google Scholar 

32. Niewiadomski, R., Pelachaud, C.: Towards multimodal expression of laughter. In: Nakano, Y., Neff, M., Paiva, A., Walker, M. (eds.) IVA 2012. LNCS, vol. 7502, pp. 231–244. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

33. Niewiadomski, R., Hofmann, J., Urbain, J., Platt, T., Wagner, J., Piot, B., Cakmak, H., Pammi, S., Baur, T., Dupont, S., Geist, M., Lingenfelser, F., McKeown, G., Pietquin, O., Ruch, W.: Laugh-aware virtual agent and its impact on user amusement. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, AAMAS 2013. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, pp. 619–626 (2013)

    Google Scholar 

34. Oura, K.: HMM-based speech synthesis system (HTS) (computer program webpage), http://hts.sp.nitech.ac.jp/ (consulted on June 22, 2011)

35. Owens, M.D.: It’s all in the game: Gamification, games, and gambling. Gaming Law Review and Economics 16 (2012)

    Google Scholar 

36. Petridis, S., Pantic, M.: Audiovisual discrimination between laughter and speech. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, Nevada, pp. 5117–5120 (2008)

    Google Scholar 

37. Petridis, S., Pantic, M.: Is this joke really funny? Judging the mirth by audiovisual laughter analysis. In: Proceedings of the IEEE International Conference on Multimedia and Expo, New York, USA, pp. 1444–1447 (2009)

    Google Scholar 

38. Poe, E.A.: Maelzel’s chess-player. In: Southern Literary Messenger, vol. 2, pp. 318–326 (1836)

    Google Scholar 

39. Qu, B., Pammi, S., Niewiadomski, R., Chollet, G.: Estimation of FAPs and intensities of AUs based on real-time face tracking. In: Pucher, M., Cosker, D., Hofer, G., Berger, M., Smith, W. (eds.) The 3rd International Symposium on Facial Analysis and Animation. ACM (2012)

    Google Scholar 

40. Ruch, W., Ekman, P.: The expressive pattern of laughter. In: Kaszniak, A. (ed.) Emotion, Qualia and Consciousness, pp. 426–443. World Scientific Publishers, Tokyo (2001)

    Chapter  Google Scholar 

41. Ruch, W., Proyer, R.: Extending the study of gelotophobia: On gelotophiles and katagelasticists. Humor-International Journal of Humor Research 22(1/2), 183–212 (2009)

    Google Scholar 

42. Ruf, T., Ernst, A., Küblbeck, C.: Face detection with the sophisticated high-speed object recognition engine (shore). In: Heuberger, A., Elst, G., Hanke, R. (eds.) Microelectronic Systems, pp. 243–252. Springer, Heidelberg (2011), http://dx.org/10.1007/978-3-642-23071-4_23

    Chapter  Google Scholar 

43. Scherer, S., Glodek, M., Schwenker, F., Campbell, N., Palm, G.: Spotting laughter in natural multiparty conversations: A comparison of automatic online and offline approaches using audiovisual data. ACM Trans. Interact. Intell. Syst. 2(1), 4:1–4:31 (2012)

    Google Scholar 

44. Sundaram, S., Narayanan, S.: Automatic acoustic synthesis of human-like laughter. Journal of the Acoustical Society of America 121, 527–535 (2007)

    Article  Google Scholar 

45. Tokuda, K., Yoshimura, T., Masuko, T., Kobayashi, T., Kitamura, T.: Speech parameter generation algorithms for hmm-based speech synthesis. In: ICASSP, pp. 1315–1318 (2000)

    Google Scholar 

46. Tokuda, K., Zen, H., Black, A.: An HMM-based speech synthesis system applied to English. In: Proceedings of the 2002 IEEE Speech Synthesis Workshop, Santa Monica, California, pp. 227–230 (2002)

    Google Scholar 

47. Truong, K.P., van Leeuwen, D.A.: Automatic discrimination between laughter and speech. Speech Communication 49, 144–158 (2007)

    Article  Google Scholar 

48. Urbain, J., Çakmak, H., Dutoit, T.: Arousal-driven synthesis of laughter. Submitted to the IEEE Journal of Selected Topics in Signal Processing, Special Issue on Statistical Parametric Speech Synthesis (2014)

    Google Scholar 

49. Urbain, J., Cakmak, H., Dutoit, T.: Development of hmm-based acoustic laughter synthesis. In: Interdisciplinary Workshop on Laughter and other Non-Verbal Vocalisations in Speech, Dublin, Ireland, pp. 26–27 (2012)

    Google Scholar 

50. Urbain, J., Cakmak, H., Dutoit, T.: Evaluation of hmm-based laughter synthesis. In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada (2013)

    Google Scholar 

51. Urbain, J., Dutoit, T.: A phonetic analysis of natural laughter, for use in automatic laughter processing systems. In: Proceedings of the Fourth Bi-annual International Conference of the HUMAINE Association on Affective Computing and Intelligent Interaction (ACII 2011), Memphis, Tennesse, pp. 397–406 (2011)

    Google Scholar 

52. Urbain, J., Niewiadomski, R., Bevacqua, E., Dutoit, T., Moinet, A., Pelachaud, C., Picart, B., Tilmanne, J., Wagner, J.: Avlaughtercycle: Enabling a virtual agent to join in laughing with a conversational partner using a similarity-driven audiovisual laughter animation. Journal on Multimodal User Interfaces 4(1), 47–58 (2010); special Issue: eNTERFACE 2009

    Google Scholar 

53. Urbain, J., Niewiadomski, R., Mancini, M., Griffin, H., Çakmak, H., Ach, L., Volpe, G.: Multimodal analysis of laughter for an interactive system. In: Mancas, M., d’ Alessandro, N., Siebert, X., Gosselin, B., Valderrama, C., Dutoit, T. (eds.) Intetain. LNICST, vol. 124, pp. 183–192. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

54. Wagner, J., Lingenfelser, F., Baur, T., Damian, I., Kistler, F., André, E.: The social signal interpretation (ssi) framework - multimodal signal processing and recognition in real-time. In: Proceedings of the 21st ACM International Conference on Multimedia, Barcelona, Spain, October 21-25 (2013)

    Google Scholar 

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