IEEE Transactions on Pattern Analysis and Machine Intelligence
Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Philips automatic train timetable information system
Speech Communication - Special issue on interactive voice technology for telecommunication applications
Grammatical Inference: An Introduction Survey
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
The TRAINS 93 Dialogues
DATE: a dialogue act tagging scheme for evaluation of spoken dialogue systems
HLT '01 Proceedings of the first international conference on Human language technology research
Dialogue management in the Mercury flight reservation system
ANLP/NAACL-ConvSyst '00 Proceedings of the 2000 ANLP/NAACL Workshop on Conversational systems - Volume 3
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
Segmented and unsegmented dialogue-act annotation with statistical dialogue models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Inference of finite-state transducers from regular languages
Pattern Recognition
Automatic annotation of dialogues using n-grams
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
A study of a segmentation technique for dialogue act assignation
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
Simultaneous dialogue act segmentation and labelling using lexical and syntactic features
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Unsupervised classification of dialogue acts using a dirichlet process mixture model
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Semi-Supervised Learning with Measure Propagation
The Journal of Machine Learning Research
Estimating the number of segments for improving dialogue act labelling
Natural Language Engineering
Discriminative framework for spoken tunisian dialect understanding
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
| Hi-index | 0.00 |
Dialogue systems are one of the most interesting applications of speech and language technologies. There have recently been some attempts to build dialogue systems in Spanish, and some corpora have been acquired and annotated. Using these corpora, statistical machine learning methods can be applied to try to solve problems in spoken dialogue systems. In this paper, two statistical models based on the maximum likelihood assumption are presented, and two main applications of these models on a Spanish dialogue corpus are shown: labelling and decoding. The labelling application is useful for annotating new dialogue corpora. The decoding application is useful for implementing dialogue strategies in dialogue systems. Both applications centre on unsegmented dialogue turns. The obtained results show that, although limited, the proposed statistical models are appropriate for these applications.