Skip to main content

A Probabilistic Approach to the Interpretation of Spoken Utterances

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5351))

Abstract

In this paper we describe Scusi?, the speech interpretation component of a spoken dialogue module designed for an autonomous robotic agent. Scusi? postulates and maintains multiple interpretations of the spoken discourse, and employs a probabilistic formalism to assess and rank hypotheses regarding the meaning of spoken utterances. These constituents in combination enable Scusi? to cope gracefully with ambiguity and speech recognition errors. The results of our evaluation are encouraging, yielding good interpretation performance for utterances of different types and lengths.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Miller, S., Stallard, D., Bobrow, R., Schwartz, R.: A fully statistical approach to natural language interfaces. In: ACL 1996 – Proceedings of the 34th Conference of the Association for Computational Linguistics, Santa Cruz, California, pp. 55–61 (1996)

    Google Scholar 

  2. Sowa, J.: Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley, Reading (1984)

    MATH  Google Scholar 

  3. Gildea, D., Jurafsky, D.: Automatic labeling of semantic roles. Computational Linguistics 28(3), 245–288 (2002)

    Article  Google Scholar 

  4. Zukerman, I., Makalic, E., Niemann, M.: Using probabilistic feature matching to understand spoken descriptions. In: AI 2008 Proceedings – the 21st Australasian Joint Conference on Artificial Intelligence, Auckland, New Zealand (2008)

    Google Scholar 

  5. George, S., Zukerman, I., Niemann, M., Marom, Y.: Considering multiple options when interpreting spoken utterances. In: Proceedings of the 5th IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems, Hyderabad, India, pp. 7–14 (2007)

    Google Scholar 

  6. Niemann, M., Zukerman, I., Makalic, E., George, S.: Hypothesis generation and maintenance in the interpretation of spoken utterances. In: Orgun, M.A., Thornton, J. (eds.) AI 2007. LNCS (LNAI), vol. 4830, pp. 466–475. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  7. Makalic, E., Zukerman, I., Niemann, M., Schmidt, D.: A probabilistic model for understanding composite spoken descriptions. In: Ho, T.-B., Zhou, Z.-H. (eds.) PRICAI 2008. LNCS (LNAI), vol. 5351, pp. 581–592. Springer, Heidelberg (2008)

    Google Scholar 

  8. Zukerman, I., George, S.: A probabilistic approach for argument interpretation. User Modeling and User-Adapted Interaction, Special Issue on Language-Based Interaction 15(1-2), 5–53 (2005)

    Article  Google Scholar 

  9. Wyatt, J.: Planning clarification questions to resolve ambiguous references to objects. In: Proceedings of the 4th IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems, Edinburgh, Scotland, pp. 16–23 (2005)

    Google Scholar 

  10. Pfleger, N., Engel, R., Alexandersson, J.: Robust multimodal discourse processing. In: Proceedings of the 7th Workshop on the Semantics and Pragmatics of Dialogue, Saarbrücken, Germany, pp. 107–114 (2003)

    Google Scholar 

  11. Hüwel, S., Wrede, B.: Spontaneous speech understanding for robust multi-modal human-robot communication. In: Proceedings of the COLING/ACL Main conference poster sessions, Sydney, Australia, pp. 391–398 (2006)

    Google Scholar 

  12. He, Y., Young, S.: A data-driven spoken language understanding system. In: ASRU 2003 – Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding, St. Thomas, US Virgin Islands, pp. 583–588 (2003)

    Google Scholar 

  13. Gorniak, P., Roy, D.: Probabilistic grounding of situated speech using plan recognition and reference resolution. In: ICMI 2005 – Proceedings of the Seventh International Conference on Multimodal Interfaces, Trento, Italy, pp. 138–143 (2005)

    Google Scholar 

  14. Knight, S., Gorrell, G., Rayner, M., Milward, D., Koeling, R., Lewin, I.: Comparing grammar-based and robust approaches to speech understanding: A case study. In: EUROSPEECH 2001 – Proceedings of the Seventh European Conference on Speech Communication and Technology, Aalborg, Denmark, pp. 1779–1782 (2001)

    Google Scholar 

  15. Matsui, T., Asoh, H., Fry, J., Motomura, Y., Asano, F., Kurita, T., Hara, I., Otsu, N.: Integrated natural spoken dialogue system of Jijo-2 mobile robot for office services. In: AAAI 1999 – Proceedings of the Sixteenth National Conference on Artificial Intelligence, Orlando, Florida, pp. 621–627 (1999)

    Google Scholar 

  16. Bos, J., Klein, E., Oka, T.: Meaningful conversation with a mobile robot. In: EACL10 – Proceedings of the 10th Conference of the European Chapter of the Association for Computational Linguistics, Budapest, Hungary, pp. 71–74 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zukerman, I., Makalic, E., Niemann, M., George, S. (2008). A Probabilistic Approach to the Interpretation of Spoken Utterances. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89197-0_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89196-3

  • Online ISBN: 978-3-540-89197-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics