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Effect of Speech Entrainment in Human-Computer Conversation: A Review

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Intelligent Human Computer Interaction (IHCI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14531))

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Abstract

The phenomenon of entrainment in conversation is the process where participants become more similar to each other in terms of different verbal and non-verbal aspects such as acoustic-prosodic, lexical, syntactic, pitch, and speech rate. This process of becoming similar to each other is the key to effective human-human conversation. To replicate the effectiveness observed in human-human conversation, it is equally critical to explore the occurrence of entrainment within human-machine conversation. This review article examines the various non-verbal and verbal aspects that machines are able to adapt for improved entrainment in human-machine conversation. Initially, we categorize the specific verbal and non-verbal behaviors of human users that machines are capable of adapting. Subsequently, we analyze the likely challenges that have prevented the speech technology sector from enabling smooth, natural interactions between humans and machines. These obstacles have hindered the industry’s ability to leverage the phenomenon of entrainment for more fluid and intuitive human-machine conversation. Finally, we advocate for a mechanomorphic design strategy in human-machine conversation, outlining the rationale for its potential efficacy.

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References

  1. Levitan, R., et al.: Implementing Acoustic-Prosodic Entrainment in a Conversational Avatar. Interspeech. vol. 16 (2016)

    Google Scholar 

  2. Gálvez, R.H., et al.: An empirical study of the effect of acoustic-prosodic entrainment on the perceived trustworthiness of conversational avatars. Speech Commun. 124, 46–67 (2020)

    Article  Google Scholar 

  3. Beňuš, Š., et al.: Prosodic entrainment and trust in human-computer interaction. In: Proceedings of the 9th International Conference on Speech Prosody. Baixas, France: International Speech Communication Association (2018)

    Google Scholar 

  4. Iio, T., et al.: Lexical entrainment in human robot interaction: do humans use their vocabulary to robots? Int. J. Soc. Robot. 7, 253–263 (2015)

    Article  Google Scholar 

  5. Huiyang, S., Min, W.: Improving interaction experience through lexical convergence: the prosocial effect of lexical alignment in human-human and human-computer interactions. Int. J. Hum. Comput. Interact. 38(1), 28–41 (2022)

    Article  Google Scholar 

  6. Nuñez, T.R., et al.: Virtual agents aligning to their users. Lexical alignment in human-agent-interaction and its psychological effects. Int. J. Hum Comput Stud. 178, 103093 (2023)

    Article  Google Scholar 

  7. Levitan, R., et al.: Entrainment and turn-taking in human-human dialogue. In: 2015 AAAI Spring Symposium Series (2015)

    Google Scholar 

  8. Linnemann, G.A., Jucks, R.: can i trust the spoken dialogue system because it uses the same words as i do?-influence of lexically aligned spoken dialogue systems on trustworthiness and user satisfaction. Interact. Comput. 30(3), 173–186 (2018)

    Article  Google Scholar 

  9. Schoot, L., Hagoort, P., Segaert, K.: Stronger syntactic alignment in the presence of an interlocutor. Front. Psychol. 10, 685 (2019)

    Article  Google Scholar 

  10. Hirschberg, J.B, Nenkova, A., Gravano, A.: High frequency word entrainment in spoken dialogue (2008)

    Google Scholar 

  11. Mori, M., MacDorman, K.F., Kageki, N.: The uncanny valley [from the field]. IEEE Robot. Autom. Mag. 19(2), 98–100 (2012)

    Article  Google Scholar 

  12. Lubold, N., Pon-Barry, H., Walker, E.: Naturalness and rapport in a pitch adaptive learning companion. In: 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU). IEEE (2015)

    Google Scholar 

  13. Balentine, B.: It’s Better to Be a Good Machine Than a Bad Person: Speech Recognition and Other Exotic User Interfaces in the Twilight of the Jetsonian Age. ICMI Press (2007)

    Google Scholar 

  14. Strömbergsson, S., et al.: Timing responses to questions in dialogue. Interspeech. vol. 2013 (2013)

    Google Scholar 

  15. Phukon, M., Shrivastava, A., Balentine, B.: Can VUI turn-taking entrain user behaviours? voice user interfaces that disallow overlapping speech present turn-taking challenges. In: Proceedings of the 13th Indian Conference on Human-Computer Interaction (2022)

    Google Scholar 

  16. Goetsu, S., Sakai, T.: Different types of voice user interface failures may cause different degrees of frustration. arXiv preprint arXiv:2002.03582 (2020)

  17. Goetsu, S., Sakai, T.: Voice input interface failures and frustration: developer and user perspectives. In: Adjunct Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (2019)

    Google Scholar 

  18. Kim, J., Jeong, M., Lee, S.C.: Why did this voice agent not understand me?" error recovery strategy for in-vehicle voice user interface. In: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings (2019)

    Google Scholar 

  19. Jiang, J., Jeng, W., He, D.: How do users respond to voice input errors? Lexical and phonetic query reformulation in voice search. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval (2013)

    Google Scholar 

  20. Luger, E., Sellen, A.: like having a really bad PA the gulfbetween user expectation and experience of conversational agents. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 5286–5297 (2016)

    Google Scholar 

  21. Tannen, D.: Talking Voices: Repetition, Dialogue, and Imagery in Conversational Discourse, vol. 26. Cambridge University Press, Cambridge (2007)

    Book  Google Scholar 

  22. Natale, M.: Convergence of mean vocal intensity in dyadic communication as a function of social desirability. J. Pers. Soc. Psychol. 32(5), 790 (1975)

    Article  Google Scholar 

  23. Heldner, M., Edlund, J., Hirschberg, J.B.: Pitch similarity in the vicinity of backchannels (2010)

    Google Scholar 

  24. Pardo, J.S.: On phonetic convergence during conversational interaction. J. Acoust. Soc. Am. 119(4), 2382–2393 (2006)

    Article  Google Scholar 

  25. Lubold, N., Pon-Barry, H.: Acoustic-prosodic entrainmentand rapport in collaborative learning dialogues. In: Proceedings of the 2014 ACMworkshop on Multimodal Learning Analytics Workshop and Grand Challenge, pp. 5–12 (2014)

    Google Scholar 

  26. Manson, J.H., et al.: Convergence of speech rate in conversation predicts cooperation. Evol. Hum. Behav. 34(6), 419–426 (2013)

    Article  Google Scholar 

  27. Wynn, C.J., et al.: Speech entrainment in adolescent conversations: a developmental perspective. J. Speech, Lang. Hearing Res. 1–19 (2023)

    Google Scholar 

  28. Wynn, C.J., Barrett, T.S., Borrie, S.A.: Rhythm perception, speaking rate entrainment, and conversational quality: a mediated model. J. Speech Lang. Hear. Res. 65(6), 2187–2203 (2022)

    Article  Google Scholar 

  29. Borrie, S.A., et al.: Syncing up for a good conversation: a clinically meaningful methodology for capturing conversational entrainment in the speech domain. J. Speech, Lang. Hearing Res. 62(2), 283–296 (2019)

    Google Scholar 

  30. Coupland, J., Coupland, N., Giles, H.: Accommodation theory. communication, context and consequences. Contexts Accommodation, 1–68 (1991)

    Google Scholar 

  31. Paletz, S.B.F., et al.: Speaking similarly: team personality composition and acoustic-prosodic entrainment. Small Group Res. 10464964231178748 (2023)

    Google Scholar 

  32. Xia, Z., Hirschberg, J., Levitan, R.: Investigating prosodic entrainment from global conversations to local turns and tones in mandarin conversations. Speech Commun. 153, 102961 (2023)

    Article  Google Scholar 

  33. Brennan, E.S.: Lexical choice and conceptual pacts in conversation. J. Exp. Psychol. Learn. Mem. Cogn. 22, 1482–1493 (1996)

    Article  Google Scholar 

  34. Shen, H., Wang, M.: Effects of social skills on lexical alignment in human-human interaction and human-computer interaction. Comput. Hum. Behav. 143, 107718 (2023)

    Article  Google Scholar 

  35. Iio, T., et al.: Lexical entrainment in human-robot interaction: can robots entrain human vocabulary?. In: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE (2009)

    Google Scholar 

  36. Cowan, B.R., Branigan, H.P., Beale, R.: Investigating the impact of interlocutor voice on syntactic alignment in human-computer dialogue. In: The 26th BCS Conference on Human Computer Interaction, vol. 26 (2012)

    Google Scholar 

  37. Beňuš, Š.: Social aspects of entrainment in spoken interaction. Cogn. Comput. 6, 802-813 (2014)

    Google Scholar 

  38. Levitan, R.: Acoustic-Prosodic Entrainment In Human-human and Human-computer Dialogue. Columbia University, New York (2014)

    Google Scholar 

  39. Levitan, R., et al.: Acoustic-prosodic entrainment and social behavior. In: Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human language Technologies (2012)

    Google Scholar 

  40. Shi, Z., Sen, P., Lipani, A.: Lexical Entrainment for Conversational Systems. arXiv preprint arXiv:2310.09651 (2023)

  41. Giles, H., Powesland, P.F.: Speech Style and Social Evaluation. Academic Press, Cambridge (1975)

    Google Scholar 

  42. Levitan, R., Hirschberg, J.B.: Measuring acoustic-prosodic entrainment with respect to multiple levels and dimensions (2011)

    Google Scholar 

  43. Cohn, M., et al.: Speech rate adjustments in conversations with an Amazon Alexa socialbot. Front. Commun. 6, 671429 (2021)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Indian Institute of Technology Guwahati, Guwahati, India

    Mridumoni Phukon & Abhishek Shrivastava

Authors
  1. Mridumoni Phukon
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  2. Abhishek Shrivastava
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Correspondence to Mridumoni Phukon .

Editor information

Editors and Affiliations

  1. Soongsil University, Seoul, Korea (Republic of)

    Bong Jun Choi

  2. Saint Louis University, St. Louis, MO, USA

    Dhananjay Singh

  3. Indian Institute of Information Technology, Allahabad, India

    Uma Shanker Tiwary

  4. Pukyong National University, Busan, Korea (Republic of)

    Wan-Young Chung

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Phukon, M., Shrivastava, A. (2024). Effect of Speech Entrainment in Human-Computer Conversation: A Review. In: Choi, B.J., Singh, D., Tiwary, U.S., Chung, WY. (eds) Intelligent Human Computer Interaction. IHCI 2023. Lecture Notes in Computer Science, vol 14531. Springer, Cham. https://doi.org/10.1007/978-3-031-53827-8_4

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  • DOI: https://doi.org/10.1007/978-3-031-53827-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-53826-1

  • Online ISBN: 978-3-031-53827-8

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