Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
Computer Speech and Language
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
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
Integrating incremental speech recognition and POMDP-based dialogue systems
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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For a spoken dialog system to make good use of a speech recognition N-Best list, it is essential to know how much trust to place in each entry. This paper presents a method for assigning a probability of correctness to each of the items on the N-Best list, and to the hypothesis that the correct answer is not on the list. We find that both multinomial logistic regression and support vector machine models yields meaningful, useful probabilities across different tasks and operating conditions.