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How to Design the Expression Ways of Conversational Agents Based on Affective Experience

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Human-Computer Interaction. Multimodal and Natural Interaction (HCII 2020)

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Abstract

With the rapid development of artificial intelligence, the technology of human-computer interaction is becoming more and more mature. The variety of terminal products equipped with conversational agents are more diverse, and the product penetration rate is also getting higher and higher. This study focused on the problems of the conversational agent in response. In this paper, we presented a study with 20 participants to explore how to design the expression ways of conversational agents’ feedback with considerations of users’ affective experience. We explored the performance of three different expression ways (general way, implicit way, and explicit way) in different time and different functions. And we examined whether users of different genders have different preferences for these three expression ways. Therefore, we used the “Wizard of Oz techniques” to simulate a real environment for communication between the user and the conversational agent. In this study, we combined quantitative scoring (five aspects: affection, confidence, naturalness, social distance, and satisfaction) with qualitative interviews. The results showed that: (1) the user’s affective experience should be considered in expression ways’ design; (2) different expression ways had different performances in different functions, and the explicit way performed better in most situations; (3) male users seemed to rate the agent’s expression performance higher than female users.

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References

  1. Yang, X., Aurisicchio, M., Baxter, W.: Understanding affective experiences with conversational agents. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019 (2019). https://doi.org/10.1145/3290605.3300772

  2. Vtyurina, A., Savenkov, D., Agichtein, E., Clarke, C.L.: Exploring conversational search with humans, assistants, and wizards, pp. 2187–2193. ACM (2017). http://dl.acm.org/citation.cfm?id=3053175

  3. Forlizzi, J., Battarbee, K.: Understanding experience in interactive systems, pp. 261–268. ACM (2004). http://dl.acm.org/citation.cfm?id=1013152

  4. Nass, C., Brave, S.: Wired of Speech. The MIT Press, Cambridge (2005)

    Google Scholar 

  5. Nass, C., Reeves, B.: The Media Equation. CSLI Publications, Stanford (1996)

    Google Scholar 

  6. Ash, M.: How Cortana comes to life in Windows 10 (2015). http://blogs.windows.com/

  7. Pearl, C.: Designing Voice User Interfaces: Principles of Conversational Experiences. O’Reilly Media Inc., Boston (2016)

    Google Scholar 

  8. Weinberger, M.: Why Microsoft doesn’t want its digital assistant, Cortana, to sound too human (2016). http://www.businesinsider.com/why-microsoftdoesnt-want-to-sound-too-human-2016-2/

  9. Cohen, M., Giangola, J., Balogh, J.: Voice User Interface Design. Addison-Wesley, Boston (2004)

    Google Scholar 

  10. Rubin, R.B., Perse, E.M., Barbato, C.A.: Conceptualization and measurement of interpersonal communication motives. Hum. Commun. Res. 14(4), 602–628 (1988)

    Article  Google Scholar 

  11. Sheng, L.: Win-Win Management Art: Social Style and Organizational Behavior. Economy & Management Publishing House Press (2002)

    Google Scholar 

  12. Slowikowski, M.K.: Using the DISC behavioral instrument to guide leadership and communication. AORN J. 82(5), 835–836, 838, 841–843 (2005)

    Google Scholar 

  13. Sugerman, J.: Using the DiSC® model to improve communication effectiveness. Ind. Commer. Train. 41(3), 151–154 (2009). https://doi.org/10.1108/00197850910950952

    Article  Google Scholar 

  14. Alpern, M., Minardo, K.: Developing a car gesture interface for use as a secondary task. In: CHI 2003 Extended Abstracts on Human Factors in Computing Systems, CHI 2003 (2003)

    Google Scholar 

  15. Bella, M., Hanington, B.: Universal Methods of Design, p. 204. Rockport Publishers, Beverly (2012)

    Google Scholar 

  16. Collisson, P.M., Hardiman, G., Santos, M.: User research makes your AI smarter. https://medium.com/microsoft-design/user-research-makes-your-ai-smarter-70f6ef6eb25a. Accessed 1 July 2019

  17. Street, R.L.: Evaluation of noncontent speech accommodation. Lang. Commun. 2(1), 13–31 (1982). https://doi.org/10.1016/0271-5309(82)90032-5

    Article  Google Scholar 

  18. Adiga, N., Prasanna, S.R.M.: Acoustic features modelling for statistical parametric speech synthesis: a review. IETE Tech. Rev. 36(2), 130–149 (2018). https://doi.org/10.1080/02564602.2018.1432422

    Article  Google Scholar 

  19. Bond, M.H.: Emotions and their expression in Chinese culture. J. Nonverbal Behav. 17(4), 245–262 (1993). https://doi.org/10.1007/bf00987240

    Article  Google Scholar 

  20. Candello, H., et al.: The effect of audiences on the user experience with conversational interfaces in physical spaces. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019 (2019)

    Google Scholar 

  21. Purington, A., Taft, J.G., Sannon, S., Bazarova, N.N., Taylor, S.H.: Alexa is my new BFF: social roles, user satisfaction, and personification of the Amazon Echo. In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 2853–2859. ACM (2017)

    Google Scholar 

  22. Yarosh, S., et al.: Children asking questions: speech interface reformulations and personifcation preferences. In: Proceedings of the 17th ACM Conference on Interaction Design and Children, pp. 300–312. ACM (2018)

    Google Scholar 

  23. @001期货网: Annual work hours. Weibo (2019). https://weibo.com/1649728202/HjehjEpvz?refer_flag=1001030103_&type=comment#_rnd1568863067626. Accessed 3 Mar 2019

  24. Wang, L., Rau, P.L.P., Evers, V., Robinson, B., Hinds, P.J.: Responsiveness to robots: effects of ingroup orientation &. ommunication style on HRI in China. In: ACM/IEEE International Conference on Human-Robot Interaction. IEEE (2009)

    Google Scholar 

  25. Rau, P.L.P., Li, Y., Li, D.: Effects of communication style and culture on ability to accept recommendations from robots. Comput. Hum. Behav. 25(2), 587–595 (2009)

    Article  Google Scholar 

  26. Apicella, C.L., Feinberg, D.R.: Voice pitch alters mate-choice-relevant perception in hunter-gatherers. Proc. Roy. Soc. B Biol. Sci. 276, 1077–1082 (2009)

    Google Scholar 

  27. Re, D.E., O’Connor, J.J., Bennett, P.J., Feinberg, D.R.: Preferences for very low and very high voice pitch in humans. PLoS ONE 7(3), e32719 (2012)

    Article  Google Scholar 

  28. Fraccaro, P.J.: Experimental evidence that women speak in a higher voice pitch to men they find attractive. J. Evol. Psychol. 9(1), 57–67 (2011)

    Article  Google Scholar 

  29. Jones, B.C., Feinberg, D.R., Watkins, C.D., Fincher, C.L., Little, A.C., DeBruine, L.M.: Pathogen disgust predicts women’s preferences for masculinity in men’s voices, faces, and bodies. Behav. Ecol. 24(2), 373–379 (2013)

    Article  Google Scholar 

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Correspondence to Ronggang Zhou .

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Zhang, C., Zhou, R., Zhang, Y., Sun, Y., Zou, L., Zhao, M. (2020). How to Design the Expression Ways of Conversational Agents Based on Affective Experience. In: Kurosu, M. (eds) Human-Computer Interaction. Multimodal and Natural Interaction. HCII 2020. Lecture Notes in Computer Science(), vol 12182. Springer, Cham. https://doi.org/10.1007/978-3-030-49062-1_21

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  • DOI: https://doi.org/10.1007/978-3-030-49062-1_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49061-4

  • Online ISBN: 978-3-030-49062-1

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