Please use this identifier to cite or link to this item: doi:10.22028/D291-23478
Title: Using logistic regression to initialise reinforcement-learning-based dialogue systems
Author(s): Rieser, Verena
Lemon, Oliver
Language: German
Year of Publication: 2006
OPUS Source: IEEE/ACL Workshop on Spoken Language Technology : (SLT) ; December 10-13, 2006. - Palm Beach, Aruba, 2006
DDC notations: 400 Language, linguistics
Publikation type: Conference Paper
Abstract: We investigate the use of logistic regression (LR) to initialise Reinforcement Learning (RL)-based dialogue systems with models of human dialogue strategies. LR produces accurate predictions and performs feature selection. We illustrate this technique in exploring human multimodal clarification strategies, observed in a Wizard-of-Oz experiment. We use it to initialise an RL-based system with features which significantly influence human behaviour. We show that the strategy applied by the human wizards is sensitive to different dialogue contexts. Furthermore we show that for predicting clarification behaviour the logistic models improve over the baseline on average twice as much as the supervised learning techniques used in previous work.
Link to this record: urn:nbn:de:bsz:291-scidok-9302
Date of registration: 4-Jan-2007
Faculty: P - Philosophische Fakultät
Department: P - Sprachwissenschaft und Sprachtechnologie
Former Department: bis SS 2016: Fachrichtung 4.7 - Allgemeine Linguistik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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