Investigating the Form-Function-Relation of the Discourse Particle “hm” in a Naturalistic Human-Computer Interaction

  • Ingo Siegert
  • Dmytro Prylipko
  • Kim Hartmann
  • Ronald Böck
  • Andreas Wendemuth
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 26)


For a successful speech-controlled human-computer interaction (HCI) the pure textual information as well as individual skills, preferences, and affective states of the user have to be known. However, verbal human interaction consists of several information layers. Apart from pure textual information, further details regarding the speaker’s feelings, believes, and social relations are transmitted. The additional information is encoded through acoustics. Especially, the intonation reveals details about the speakers communicative relation and their attitude towards the ongoing dialogue.

Since the intonation is influenced by semantic and grammatical information, it is advisable to investigate the intonation of so-called discourse particles (DPs) as “hm” or “uhm”. They cannot be inflected but can be emphasised. DPs have the same intonation curves (pitch-contours) as whole sentences and thus may indicate the same functional meanings. For German language J. E. Schmidt empirically discovered seven types of form-function-concurrences on the isolated DP “hm”.

To determine the function within the dialogue of the DPs, methods are needed that preserve pitch-contours and are feasible to assign defined form-prototypes. Furthermore, it must be investigated which pitch-contours occur in naturalistic HCI and whether these contours are congruent with the findings by linguists.

In this paper we present first results on the extraction and correlation of the DP “hm”. We investigate the different form-function-relations in the naturalistic LAST MINUTE corpus and determine expectable formfunction relations in naturalistic HCI in general.


Prosodic Analysis Companion Systems Human-Computer Interaction Discourse Particle Pitch Classification 


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  1. 1.
    Allwood, J., Nivre, J., Ahlsn, E.: On the semantics and pragmatics of linguistic feedback. Journal of Semantics 9(1), 1–26 (1992)CrossRefGoogle Scholar
  2. 2.
    Benus, S., Gravana, A., Hirschberg, J.: The Prosody of Backchannels in American Englisch. In: Proceedings of the 16th International Congress of Phonetic Sciences, Saarbrcken, Germany, pp. 1065–1068 (2007)Google Scholar
  3. 3.
    Fischer, K., Wrede, B., Brindpke, C., Johanntokrax, M.: Quantitative und funktionale Analysen von Diskurspartikeln im Computer Talk. International Journal for Language Data Processing 20(1-2), 85–100 (1996)Google Scholar
  4. 4.
    Gerhard, D.: Pitch Extraction and Fundamental Frequency: History and Current Techniques. Tech. Rep. TR-CS 2003-06, Regina, Saskatchewan, Canada (2003)Google Scholar
  5. 5.
    Kehrein, R., Rabanus, S.: Ein Modell zur funktionalen Beschreibung von Diskurspartikeln. In: Neue Wege der Intonationsforschung. Germanistische Linguistik, vol. 157-158, pp. 33–50. Georg Olms Verlag, Hildesheim (2001)Google Scholar
  6. 6.
    Krippendorff, K.: Content Analysis: An Introduction to Its Methodology, 3rd edn. SAGE Publications, Thousand Oaks (2012)Google Scholar
  7. 7.
    Ladd, R.D.: Intonational Phonology. Studies in Linguistics, vol. 79. Cambridge University Press (1996)Google Scholar
  8. 8.
    Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33, 159–174 (1977)CrossRefzbMATHMathSciNetGoogle Scholar
  9. 9.
    Lange, J., Frommer, J.: Subjektives Erleben und intentionale Einstellung in Interviews zur Nutzer-Companion-Interaktion (Subjective experience and intentional setting within intervies of User-Companion-Interaction). In: Informatik 2011: Informatik schafft Communities, Beitrge der 41. Jahrestagung der GI. Lecture Notes in Informatics, vol. 192, p. 240 (2011)Google Scholar
  10. 10.
    Rabiner, L., Cheng, M.J., Rosenberg, A.E., McGonegal, C.A.: A comparative performance study of several pitch detection algorithms. IEEE Trans. on ASSP 24, 399–417 (1976)CrossRefGoogle Scholar
  11. 11.
    Rösner, D., Friesen, R., Otto, M., Lange, J., Haase, M., Frommer, J.: Intentionality in interacting with companion systems – an empirical approach. In: Jacko, J.A. (ed.) Human-Computer Interaction, Part III, HCII 2011. LNCS, vol. 6763, pp. 593–602. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    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
  13. 13.
    Schuller, B., Batliner, A., Steidl, S., Seppi, D.: Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge. Speech Commun. 53(9-10), 1062–1087 (2011)CrossRefGoogle Scholar
  14. 14.
    Siegert, I., Böck, R., Wendemuth, A.: The influence of context knowledge for multimodal annotation on natural material. In: Proc. of the First Workshop on Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction (MA3), Santa Cruz, USA (2012)Google Scholar
  15. 15.
    Ward, N.: Pragmatic functions of prosodic features in non-lexical utterances. In: Proceedings of Speech Prosody 2004, Nara, Japan, pp. 325–328 (2004)Google Scholar
  16. 16.
    Wendemuth, A., Biundo, S.: A Companion Technology for Cognitive Technical Systems. In: Esposito, A., Esposito, A.M., Vinciarelli, A., Hoffmann, R., Müller, V.C. (eds.) COST 2102. LNCS, vol. 7403, pp. 89–103. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  17. 17.
    Zeng, Z., Pantic, M., Roisman, G.I., Huang, T.S.: A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions. IEEE Trans. on Pattern Analysis and Machine Intelligence 31, 39–58 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ingo Siegert
    • 1
  • Dmytro Prylipko
    • 1
  • Kim Hartmann
    • 1
  • Ronald Böck
    • 1
  • Andreas Wendemuth
    • 1
  1. 1.Cognitive Systems GroupOtto von Guericke University MagdeburgMagdeburgGermany

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