Natural language generation as planning under uncertainty for spoken dialogue systems

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

16 Citations (Scopus)

Abstract

We present and evaluate a new model for Natural Language Generation (NLG) in Spoken Dialogue Systems, based on statistical planning, given noisy feedback from the current generation context (e.g. a user and a surface realiser). The model is adaptive and incremental at the turn level, and optimises NLG actions with respect to a data-driven objective function. We study its use in a standard NLG problem: how to present information (in this case a set of search results) to users, given the complex trade-offs between utterance length, amount of information conveyed, and cognitive load. We set these trade-offs in an objective function by analysing existing match data. We then train a NLG policy using Reinforcement Learning (RL), which adapts its behaviour to noisy feedback from the current generation context. This policy is compared to several baselines derived from previous work in this area. The learned policy significantly outperforms all the prior approaches. © 2010 Springer-Verlag Berlin Heidelberg.

Original languageEnglish
Title of host publicationEmpirical Methods in Natural Language Generation - Data-Oriented Methods and Empirical Evaluation
Pages105-120
Number of pages16
Volume5790 LNAI
DOIs
Publication statusPublished - 2010
Event12th European Workshop on Natural Language Generation - Athens, Greece
Duration: 30 Mar 20093 Apr 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5790 LNAI
ISSN (Print)0302-9743

Conference

Conference12th European Workshop on Natural Language Generation
Abbreviated titleENLG 2009
CountryGreece
CityAthens
Period30/03/093/04/09

Keywords

  • Adaptivity
  • data-driven methods
  • Incremental NLG
  • Information Presentation
  • Optimisation
  • Reinforcement Learning
  • Spoken Dialogue Systems

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  • Cite this

    Rieser, V., & Lemon, O. (2010). Natural language generation as planning under uncertainty for spoken dialogue systems. In Empirical Methods in Natural Language Generation - Data-Oriented Methods and Empirical Evaluation (Vol. 5790 LNAI, pp. 105-120). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5790 LNAI). https://doi.org/10.1007/978-3-642-15573-4_6