Computational Linguistics & Phonetics Computational Linguistics & Phonetics Fachrichtung 4.7 Universität des Saarlandes

Spoken Dialogue Systems

Softwareprojekt: Computerlinguistik, B.Sc./M.Sc.

Leitung: Klakow, Wolska
Ort: wird noch bekannt gegeben
Zeit: wird noch bekannt gegeben
Beginn: wird noch bekannt gegeben
Geeignet für: B.Sc./M.Sc.

In this course we plan to explore methods to learn dialog strategies. For this, reinforcement learning has turned out to be very popular in the past years. The rough plan is

  • study methods for reinforcement learning
  • implement them for a text book example
  • adapt the method to a dialog task

    Literatur

  • R. Sutton and A. Barto "Reinforcement Learning: An Introduction" HTML
  • S. Singh, D. Litman, M. Kearns and M. Walker "Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System"
  • James Henderson, Oliver Lemon, and Kallirroi Georgila "Hybrid Reinforcement/Supervised Learning for Dialogue Policies from COMMUNICATOR data", IJCAI workshop 2005
  • Kallirroi Georgila and Oliver Lemon and James Henderson, "Automatic annotation of COMMUNICATOR dialogue data for learning dialogue strategies and user simulations", 9th SEMDIAL, DIALOR, 2005

    Bemerkungen/Voraussetzungen
    If you are interested in this course, drop us a mail (magda@CoLi.Uni-SB.DE, dietrich@CoLi.Uni-SB.DE).

    Scheine
    Credits are awarded upon successful completion of practical work and a final presentation. For the software project, a written report together with a description of the code and the code itself are required.

    Leistungspunkte
    Bachelor: 12 CP; Master: 8 CP

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