Skip to main content
×
Home
    • Aa
    • Aa

Estimating the number of segments for improving dialogue act labelling

  • VICENT TAMARIT (a1), CARLOS-D. MARTÍNEZ-HINAREJOS (a1) and JOSÉ-MIGUEL BENEDÍ (a1)
Abstract
Abstract

In dialogue systems it is important to label the dialogue turns with dialogue-related meaning. Each turn is usually divided into segments and these segments are labelled with dialogue acts (DAs). A DA is a representation of the functional role of the segment. Each segment is labelled with one DA, representing its role in the ongoing discourse. The sequence of DAs given a dialogue turn is used by the dialogue manager to understand the turn. Probabilistic models that perform DA labelling can be used on segmented or unsegmented turns. The last option is more likely for a practical dialogue system, but it provides poorer results. In that case, a hypothesis for the number of segments can be provided to improve the results. We propose some methods to estimate the probability of the number of segments based on the transcription of the turn. The new labelling model includes the estimation of the probability of the number of segments in the turn. We tested this new approach with two different dialogue corpora: SwitchBoard and Dihana. The results show that this inclusion significantly improves the labelling accuracy.

Copyright
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

L. Dybkjaer and W. Minker 2008. Recent Trends in Discourse and Dialogue, vol. 39 of Text, Speech and Language Technology. Springer.

C. D. Martínez-Hinarejos , R. Granell , and J. M. Benedí 2006. Segmented and unsegmented dialogue-act annotation with statistical dialogue models. In Proceedings of the COLING/ACL 2006 Main Conference Poster Sesions, Sydney, Australia, pp. 563–70.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Natural Language Engineering
  • ISSN: 1351-3249
  • EISSN: 1469-8110
  • URL: /core/journals/natural-language-engineering
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Metrics

Full text views

Total number of HTML views: 1
Total number of PDF views: 5 *
Loading metrics...

Abstract views

Total abstract views: 52 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 28th May 2017. This data will be updated every 24 hours.