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InProceedings (Aufsatz / Paper einer Konferenz etc.) zugänglich unter
URN: urn:nbn:de:bsz:291-scidok-9302
URL: http://scidok.sulb.uni-saarland.de/volltexte/2007/930/


Using logistic regression to initialise reinforcement-learning-based dialogue systems

Rieser, Verena ; Lemon, Oliver

Quelle: (2006) IEEE/ACL Workshop on Spoken Language Technology : (SLT) ; December 10-13, 2006. - Palm Beach, Aruba, 2006
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Dokument 1.pdf (326 KB)

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Institut: Fachrichtung 4.7 - Allgemeine Linguistik
DDC-Sachgruppe: Sprachwissenschaft, Linguistik
Dokumentart: InProceedings (Aufsatz / Paper einer Konferenz etc.)
Sprache: Deutsch
Erstellungsjahr: 2006
Publikationsdatum: 04.01.2007
Kurzfassung auf Englisch: 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.

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