Advertisement

Discourse Particles in Human-Human and Human-Computer Interaction – Analysis and Evaluation

  • Ingo Siegert
  • Julia Krüger
  • Matthias Haase
  • Alicia Flores Lotz
  • Stephan Günther
  • Jörg Frommer
  • Dietmar Rösner
  • Andreas Wendemuth
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9731)

Abstract

Discourse particles are verifiably used in both human-human interaction (HHI) and human-computer interaction (HCI). In both types of interaction form-function-relations could be confirmed. Also correlations with specific subject characteristics, personality traits and the use of these particles could be uncovered. But these investigations are performed on separated datasets containing either HHI or HCI. Moreover, the subjects analyzed in both interaction types are not the same and thus, direct connections could not be made.

In our contribution, we report about analyses of discourse particles in both HHI and HCI with the same subjects. This enables us to draw conclusions of the communication partner’s influence in relation to subject characteristics and personality traits. This will prospectively help to better understand the use of discourse particles. By using this knowledge, future technical systems can react to known subjects more individually.

Keywords

Human-human interaction Human-computer interaction Discourse particles Personality Subject characteristics 

Notes

Acknowledgments

The work presented was done within the Transregional Collaborative Research Centre SFB/TRR 62 “Companion-Technology for Cognitive Technical Systems” (www.sfb-trr-62.de) funded by the German Research Foundation (DFG).

References

  1. 1.
    Allwood, J., Nivre, J., Ahlsén, E.: On the semantics and pragmatics of linguistic feedback. J. Semant. 9, 1–26 (1992)CrossRefGoogle Scholar
  2. 2.
    Benus, S., Gravana, A., Hirschberg, J.: The prosody of backchannels in American English. In: Proceedings of the 16th ICPhS, pp. 1065–1068. Saarbrücken (2007)Google Scholar
  3. 3.
    Bruder, C., Clemens, C., Glaser, C., Karrer-Gauß, K.: TA-EG - Fragebogen zur Erfassung von Technikaffinität. Technical report, TU Berlin (2009)Google Scholar
  4. 4.
    Corley, M., Stewart, O.W.: Hesitation disfluencies in spontaneous speech: the meaning of um. Lang. Linguist. Compass 2, 589–602 (2008)CrossRefGoogle Scholar
  5. 5.
    Costa, P.T., McCrae, R.R.: Domains and facets: hierarchical personality assessment using the revised NEO personality inventory. J. Pers. Assess. 64, 21–50 (1995)CrossRefGoogle Scholar
  6. 6.
    Fischer, K.: From Cognitive Semantics to Lexical Pragmatics. Mouton & Co, Berlin (2000)CrossRefGoogle Scholar
  7. 7.
    Fischer, K., Wrede, B., Brindöpke, C., Johanntokrax, M.: Quantitative und funktionale Analysen von Diskurspartikeln im Computer Talk. Int. J. Lang. Data Process. 20, 85–100 (1996)Google Scholar
  8. 8.
    Frommer, J., Michaelis, B., Rösner, D., Wendemuth, A., Friesen, R., Haase, M., Kunze, M., Andrich, R., Lange, J., Panning, A., Siegert, I.: Towards emotion and affect detection in the multimodal last minute corpus. In: Proceedings of the 8th LREC, pp. 3064–3069. Istanbul (2012)Google Scholar
  9. 9.
    Giles, H., Coupland, N.: Language: Contexts and Consequences. Cengage Learning, Boston (1991)Google Scholar
  10. 10.
    Horowitz, L.M., Strauß, B., Kordy, H.: Inventar zur Erfassung interpersonaler Probleme (IIPD), 2nd edn. Beltz, Weinheim (2000)Google Scholar
  11. 11.
    Jahnke, W., Erdmann, G., Kallus, K.: Stressverarbeitungsfragebogen mit SVF 120 und SVF 78, 3rd edn. Hogrefe, Göttingen (2002)Google Scholar
  12. 12.
    Kehrein, R., Rabanus, S.: Ein Modell zur funktionalen Beschreibungvon Diskurspartike. ln: Neue Wege der Intonationsforschung,Germanistische Linguistik, vol. 157–158, pp. 33–50. Georg OlmsVerlag, Hildesheim (2001)Google Scholar
  13. 13.
    Krüger, J., Wahl, M., Frommer, J.: Making the system a relational partner: users’ ascriptions in individualization-focused interactions with companion-systems. In: Proceedings of the 8th CENTRIC 2015, pp. 48–54. Barcelona (2015)Google Scholar
  14. 14.
    Lange, J., Frommer, J.: Subjektives Erleben und intentionale Einstellung in Interviews zur Nutzer-Companion-Interaktion. In: Proceedings der 41.GI-Jahrestagung. Lecture Notes in Computer Science, vol. 192, pp. 240–254. Bonner Köllen Verlag, Berlin (2011)Google Scholar
  15. 15.
    Lotz, A.F., Siegert, I., Wendemuth, A.: Automatic differentiation of form-function-relations of the discourse particle “HM” in a naturalistic human-computer interaction. In: Proceedings of the 26th ESSV, pp. 172–179. Eichstätt, Germany (2015)Google Scholar
  16. 16.
    NIST, SEMATECH: e-handbook of statistical methods (2014). http://www.itl.nist.gov/div898/handbook/
  17. 17.
    Paschen, H.: Die Funktion der Diskurspartikel HM. Master’s thesis, University Mainz (1995)Google Scholar
  18. 18.
    Poppe, P., Stiensmeier-Pelster, J., Pelster, A.: Attributionsstilfragebogen für Erwachsene (ASF-E). Hogrefe, Göttingen (2005)Google Scholar
  19. 19.
    Rösner, D., Haase, M., Bauer, T., Günther, S., Krüger, J., Frommer, J.: Desiderata for the design of companion systems - insights from a large scale wizard of Oz experiment. Künstliche Intelligenz 30(1), 53–61 (2016)CrossRefGoogle Scholar
  20. 20.
    Rösner, D., Frommer, J., Friesen, R., Haase, M., Lange, J., Otto, M.: LAST MINUTE: a multimodal corpus of speech-based user-companion interactions. In: Proceedings of the 8th LREC, pp. 96–103. Istanbul (2012)Google Scholar
  21. 21.
    Rösner, D., Kunze, M., Otto, M., Frommer, J.: Linguistic analyses of the LAST MINUTE corpus. In: Jancsary, J. (ed.) Proceedings of KONVENS 2012, pp. 145–154. ÖGAI , Main track: oral presentations, September 2012Google Scholar
  22. 22.
    Schmidt, J.E.: Bausteine der Intonation. In: Neue Wege der Intonationsforschung, Germanistische Linguistik, vol. 157–158, pp. 9–32. Georg Olms Verlag, Hildesheim (2001)Google Scholar
  23. 23.
    Selting, M., Auer, P., Barth-Weingarten, D., Bergmann, J.R., Bergmann, P., Birkner, K., Couper-Kuhlen, E., Deppermann, A., Gilles, P., Günthner, S., Hartung, M., Kern, F., Mertzlufft, C., Meyer, C., Morek, M., Oberzaucher, F., Peters, J., Quasthoff, U., Schütte, W., Stukenbrock, A., Uhmann, S.: Gesprächsanalytisches Transkriptionssystem 2 (GAT 2). Gesprächsforschung 10, 353–402 (2009)Google Scholar
  24. 24.
    Siegert, I., Haase, M., Prylipko, D., Wendemuth, A.: Discourse particles and user characteristics in naturalistic human-computer interaction. In: Kurosu, M. (ed.) HCI 2014, Part II. LNCS, vol. 8511, pp. 492–501. Springer, Heidelberg (2014)Google Scholar
  25. 25.
    Siegert, I., Hartmann, K., Philippou-Hübner, D., Wendemuth, A.: Human behaviour in HCI: complex emotion detection through sparse speech features. In: Salah, A.A., Hung, H., Aran, O., Gunes, H. (eds.) HBU 2013. LNCS, vol. 8212, pp. 246–257. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  26. 26.
    Siegert, I., Philippou-Hübner, D., Hartmann, K., Böck, R., Wendemuth, A.: Investigation of speaker group-dependent modelling for recognition of affective states from speech. Cogn. Comput. 6(4), 892–913 (2014)CrossRefGoogle Scholar
  27. 27.
    Siegert, I., Prylipko, D., Hartmann, K., Bück, R., Wendemuth, A.: Investigating the form-function-relation of the discourse particle “HM” in a naturalistic human-computer interaction. In: Bassis, S., Esposito, A., Morabito, F.C. (eds.) Recent Advances of Neural Networks Models and Applications. SIST, vol. 26, pp. 387–394. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  28. 28.
    Skantze, G., Johansson, M., Beskow, J.: Exploring turn-taking cues in multi-party human-robot discussions about objects. In: Proceedings of the 2015 ACM International Conference on Multimodal Interaction, pp. 67–74 (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ingo Siegert
    • 1
  • Julia Krüger
    • 2
  • Matthias Haase
    • 2
  • Alicia Flores Lotz
    • 1
  • Stephan Günther
    • 3
  • Jörg Frommer
    • 2
  • Dietmar Rösner
    • 3
    • 4
  • Andreas Wendemuth
    • 1
    • 4
  1. 1.Institute of Information and Communication EngineeringOtto von Guericke UniversityMagdeburgGermany
  2. 2.Department of Psychosomatic Medicine and PsychotherapyOtto von Guericke UniversityMagdeburgGermany
  3. 3.Institute of Knowledge and Language EngineeringOtto von Guericke UniversityMagdeburgGermany
  4. 4.Center for Behavioral Brain SciencesOtto von Guericke UniversityMagdeburgGermany

Personalised recommendations