The Philips automatic train timetable information system
Speech Communication - Special issue on interactive voice technology for telecommunication applications
Speech Communication - Special issue on interactive voice technology for telecommunication applications (IVITA '96)
Evaluating a Probabilistic Dialogue Model for a Railway Information Task
TSD '02 Proceedings of the 5th International Conference on Text, Speech and Dialogue
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Current and New Directions in Discourse and Dialogue
Computational Linguistics
Inference of finite-state transducers from regular languages
Pattern Recognition
Statistical framework for a Spanish spoken dialogue corpus
Speech Communication
A study of a segmentation technique for dialogue act assignation
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
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The development of a dialogue system for any task implies the acquisition of a dialogue corpus in order to study the structure of the dialogues used in that task This structure is reflected in the dialogue system behaviour, which can be rule-based or corpus-based In the case of corpus-based dialogue systems, the behaviour is defined by statistical models which are inferred from an annotated corpus of dialogues This annotation task is usually difficult and expensive, and therefore, automatic dialogue annotation tools are necessary to reduce the annotation effort An automatic dialogue labeller technique that is based on n-grams is presented in this work Its different variants are evaluated with respect to manual human annotations of a dialogue corpus devoted to train queries.