Stochastic dependency parsing of spontaneous Japanese spoken language
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Japanese dialogue corpus of multi-level annotation
SIGDIAL '00 Proceedings of the 1st SIGdial workshop on Discourse and dialogue - Volume 10
Development of a machine learnable discourse tagging tool
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Why We Twitter: An Analysis of a Microblogging Community
Advances in Web Mining and Web Usage Analysis
Hi-index | 0.00 |
This paper proposes a method of speech intention understanding based on dialogue examples. The method uses a spoken dialogue corpus with intention tags to regard the intention of each input utterance as that of the sentence to which it is the most similar in the corpus. The degree of similarity is calculated according to the degree of correspondence in morphemes and dependencies between sentences, and it is weighted by the dialogue context information. An experiment on inference of utterance intentions using a large-scale in-car spoken dialogue corpus of CIAIR has shown 68.9% accuracy. Furthermore, we have developed a prototype system of in-car spoken dialogue processing for a restaurant retrieval task based on our method, and confirmed the feasiblity of the system.