Out-of-Domain Slot Value Detection for Spoken Dialogue Systems with Context Information

Yuka Kobayashi, Takami Yoshida, Kenji Iwata, Hiroshi Fujimura, Masami Akamine

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper proposes an approach to detecting-of-domain slot values from user utterances in spoken dialogue systems based on contexts. The approach detects keywords of slot values from utterances and consults domain knowledge (i.e., an ontology) to check whether the keywords are-of-domain. This can prevent the systems from responding improperly to user requests. We use a Recurrent Neural Network (RNN) encoder-decoder model and propose a method that uses only in-domain data. The method replaces word embedding vectors of the keywords corresponding to slot values with random vectors during training of the model. This allows using context information. The model is robust against over-fitting problems because it is independent of the slot values of the training data. Experiments show that the proposed method achieves a 65% gain in F1 score relative to a baseline model and a further 13 percentage points by combining with other methods.

Original languageEnglish
Title of host publication2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages854-861
Number of pages8
ISBN (Electronic)9781538643341
DOIs
Publication statusPublished - 2019 Feb 11
Externally publishedYes
Event2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Athens, Greece
Duration: 2018 Dec 182018 Dec 21

Publication series

Name2018 IEEE Spoken Language Technology Workshop, SLT 2018 - Proceedings

Conference

Conference2018 IEEE Spoken Language Technology Workshop, SLT 2018
CountryGreece
CityAthens
Period18/12/1818/12/21

Keywords

  • Spoken dialogue system
  • random vector
  • sequence labeling
  • slot filling

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Linguistics and Language

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