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Recent research advances in Reinforcement Learning in Spoken Dialogue Systems

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Publicado en:The Knowledge Engineering Review vol. 24, no. 4 (Dec 2009), p. 375-408
Autor principal: Frampton, Matthew
Otros Autores: Lemon, Oliver
Publicado:
Cambridge University Press
Materias:
Information technology
User interface
Voice recognition
Machine learning
Research
Simulation
Design
Probability
Markov analysis
Interactive computer systems
Artificial intelligence
Acceso en línea:Citation/Abstract
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Resumen:This paper will summarize and analyze the work of the different research groups who have recently made significant contributions in using Reinforcement Learning techniques to learn dialogue strategies for Spoken Dialogue Systems (SDSs). This use of stochastic planning and learning has become an important research area in the past 10 years, since it promises automatic data-driven optimization of the behavior of SDSs that were previously hand-coded by expert developers. We survey the most important developments in the field, compare and contrast the different approaches, and describe current open problems. [PUBLICATION ABSTRACT]
ISSN:0269-8889
1469-8005
DOI:10.1017/S0269888909990166
Fuente:ABI/INFORM Global