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SIGDIAL
2010
13 years 2 months ago
Sparse Approximate Dynamic Programming for Dialog Management
Spoken dialogue management strategy optimization by means of Reinforcement Learning (RL) is now part of the state of the art. Yet, there is still a clear mismatch between the comp...
Senthilkumar Chandramohan, Matthieu Geist, Olivier...
AIMSA
2006
Springer
13 years 8 months ago
Machine Learning for Spoken Dialogue Management: An Experiment with Speech-Based Database Querying
Although speech and language processing techniques achieved a relative maturity during the last decade, designing a spoken dialogue system is still a tailoring task because of the ...
Olivier Pietquin
ICMCS
2006
IEEE
141views Multimedia» more  ICMCS 2006»
13 years 10 months ago
Consistent Goal-Directed User Model for Realisitc Man-Machine Task-Oriented Spoken Dialogue Simulation
Because of the great variability of factors to take into account, designing a spoken dialogue system is still a tailoring task. Rapid design and reusability of previous work is ma...
Olivier Pietquin
ICASSP
2008
IEEE
13 years 11 months ago
Using dialogue acts to learn better repair strategies for spoken dialogue systems
Repair or error-recovery strategies are an important design issue in Spoken Dialogue Systems (SDSs) - how to conduct the dialogue when there is no progress (e.g. due to repeated A...
Matthew Frampton, Oliver Lemon
CSL
2012
Springer
12 years 10 days ago
Reinforcement learning for parameter estimation in statistical spoken dialogue systems
Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estim...
Filip Jurcícek, Blaise Thomson, Steve Young