Detecting Uncertainty in Spoken Dialogues: An Exploratory Research for the Automatic Detection of Speaker Uncertainty by Using Prosodic Markers

Part of the Text, Speech and Language Technology book series (TLTB, volume 45)


This paper reports results in automatic detection of speaker uncertainty in spoken dialogues by using prosodic markers. For this purpose a substantial part of the AMI corpus (a multi-modal multi-party meeting corpus) has been selected and converted to a suitable format so its data could be analyzed for a selected set of prosodic features. In the absence of relevant stance annotations on (un)certainty, lexical markers (hedges) have been used to mark utterances as (un)certain. Results show that prosodic features can indeed be used to detect speaker uncertainty in spoken dialogues. The classifiers can tell uncertain from neutral utterances with an accuracy of 75% which is 25% over the baseline.


Speaker’s epistemic stance Dialogue corpus analysis Machine learning 



This work is supported by the European IST Programme Project FP6-033812. This article only reflects the authors’ views and funding agencies are not liable for any use that may be made of the information contained herein.


  1. 1.
    Ainley, J. 1988. Perceptions of teachers’ questioning styles. In 12th International Conference for the Psychology of Mathematics Education, 99–99, Vezprém, Hungary.Google Scholar
  2. 2.
    Carletta, J. C. 2007. Unleashing the killer corpus: Experiences in creating the multi-everything AMI meeting corpus. Language Resources and Evaluation 41(2):181–190.CrossRefGoogle Scholar
  3. 3.
    Bhatt, K., M. Evens, and S. Argamon. 2004. Hedged responses and expressions of affect in human/human and human/computer tutorial interactions. In 26th Annual Meeting of the Cognitive Science Society, Chicago, Illinois.Google Scholar
  4. 4.
    Boersma, P., and Weenink, D. 2008. Praat: Doing phonetics by computer. Version 5.0.06 [Software]. Available:
  5. 5.
    Brennan, S. E., and M. Williams. 1995. The feeling of another’s knowing: Prosody and filled pauses as clues to listeners about the metacognitive states of speakers. Journal of Memory and Language 34:383–398.CrossRefGoogle Scholar
  6. 6.
    Hart, J. T. 1965. Memory and the feeling-of-knowing experience. Journal of Educational Psychology 56:208–216.CrossRefGoogle Scholar
  7. 7.
    Krahmer, E., and Swerts, M. 2005. How children and adults signal and detect uncertainty in audovisual speech. Language and Speech 48(1):29–54.CrossRefGoogle Scholar
  8. 8.
    Liscombe, J., J. Hirschberg, and J. J. Venditti. 2005. Detecting certainness in spoken tutorial dialogues. In 9th European Conference on Speech Communication and Technology, 1837–1840. Lisbon.Google Scholar
  9. 9.
    Ozuru, Y., and W. Hirst. 2006. Surface features of utterances, credibility judgments, and memory. Memory & Cognition 34:1512–1526.CrossRefGoogle Scholar
  10. 10.
    Rietveld, A. C. M., and V. J. Van Heuven. 1997. Algemene Fonetiek. Bussum: Uitgeverij Coutinho.Google Scholar
  11. 11.
    Rowland, T. 1995. Hedges in mathematics talk: Linguistic pointers to uncertainty. Educational Studies in Mathematics 29:327–353.CrossRefGoogle Scholar
  12. 12.
    Smith, V. L., and H. H. Clark. 1993. On the course of answering questions. Journal of Memory and Language 32:25–38.CrossRefGoogle Scholar
  13. 13.
    Witten, I. H., and E. Frank. 2005. Data Mining: Practical Machine Learning Tools and Techniques, 2nd ed. San Francisco: Morgan Kaufmann.MATHGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.University of TwenteEnschedeThe Netherlands

Personalised recommendations