Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
A general, abstract model of incremental dialogue processing
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Incremental dialogue processing in a micro-domain
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Assessing and improving the performance of speech recognition for incremental systems
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
Computer Speech and Language
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Estimating probability of correctness for ASR N-best lists
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems
Computer Speech and Language
Stability and accuracy in incremental speech recognition
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
An empirical evaluation of a statistical dialog system in public use
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Collaborative health care plan support
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Situated incremental natural language understanding using Markov Logic Networks
Computer Speech and Language
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The goal of this paper is to present a first step toward integrating Incremental Speech Recognition (ISR) and Partially-Observable Markov Decision Process (POMDP) based dialogue systems. The former provides support for advanced turn-taking behavior while the other increases the semantic accuracy of speech recognition results. We present an Incremental Interaction Manager that supports the use of ISR with strictly turn-based dialogue managers. We then show that using a POMDP-based dialogue manager with ISR substantially improves the semantic accuracy of the incremental results.