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  • Khojah, Ranim, et al. (author)
  • Evaluating N-best Calibration of Natural Language Understanding for Dialogue Systems
  • 2022
  • In: Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2022, 07-09 September 2022, Edinburgh, UK. - Stroudsburg, PA : Association for Computational Linguistics. - 9781955917667
  • Conference paper (peer-reviewed)abstract
    • A Natural Language Understanding (NLU) component can be used in a dialogue system to perform intent classification, returning an N-best list of hypotheses with corresponding confidence estimates. We perform an in-depth evaluation of 5 NLUs, focusing on confidence estimation. We measure and visualize calibration for the 10 best hypotheses on model level and rank level, and also measure classification performance. The results indicate a trade-off between calibration and performance. In particular, Rasa (with Sklearn classifier) had the best calibration but the lowest performance scores, while Watson Assistant had the best performance but a poor calibration.
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  • Result 1-1 of 1
Type of publication
conference paper (1)
Type of content
peer-reviewed (1)
Author/Editor
Larsson, Staffan, 19 ... (1)
Berman, Alexander, 1 ... (1)
Khojah, Ranim (1)
University
University of Gothenburg (1)
Language
English (1)
Research subject (UKÄ/SCB)
Natural sciences (1)
Engineering and Technology (1)
Year
2022 (1)

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