Title :
Evaluation of dialogue act recognition approaches
Author :
Pavel Kral;Tomas Pavelka;Christophe Cerisara
Author_Institution :
Dept. Informatics & Computer Science, University of West Bohemia, Plze?, Czech Republic
Abstract :
This paper deals with automatic dialogue act recognition. Dialogue acts (DAs) are utterance-level labels that represent different states of a dialogue, such as questions, statements, hesitations, etc. Information about actual DA can be seen as the first level of dialogue understanding. The main goal of this paper is to compare our dialogue act recognition approaches that model the utterance structure, and are particularly useful when the DA corpus is small, with n-gram based approaches. Our best approach is also combined successfully with prosodic models. We further show that sentence structure-based approaches significantly outperform n-gram based methods.
Keywords :
"Natural languages","Informatics","Computer science","Automatic speech recognition","Labeling","Telephony","Taxonomy","Target recognition"
Conference_Titel :
Machine Learning for Signal Processing, 2008. MLSP 2008. IEEE Workshop on
Print_ISBN :
978-1-4244-2375-0
Electronic_ISBN :
2378-928X
DOI :
10.1109/MLSP.2008.4685529