The Philips automatic train timetable information system
Speech Communication - Special issue on interactive voice technology for telecommunication applications
Parsing inside-out
Robust grammatical analysis for spoken dialogue systems
Natural Language Engineering
Using an annotated corpus as a stochastic grammar
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
A state-transition grammar for data-oriented parsing
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
A DOP model for semantic interpretation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
A probabilistic corpus-driven model for lexical-functional analysis
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
The intersection of finite state automata and definite clause grammars
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A computational model of language performance: Data Oriented Parsing
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
Computational complexity of probabilistic disambiguation by means of tree-grammars
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Natural Language Engineering
An improved parser for data-oriented lexical-functional analysis
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Hi-index | 0.00 |
We show how the DOP model can be used for fast and robust context-sensitive processing of spoken input in a practical spoken dialogue system called OVIS. OVIS (Openbaar Vervoer Informatie Systeem) – ‘Public Transport Information System’, is a Dutch spoken language information system which operates over ordinary telephone lines. The prototype system is the immediate goal of the NWO Priority Programme ‘Language and Speech Technology’. In this paper, we extend the original Data-Oriented Parsing (DOP) model to context-sensitive interpretation of spoken input. The system we describe uses the OVIS corpus (which consists of 10,000 trees enriched with compositional semantics) to compute from an input word-graph the best utterance together with its meaning. Dialogue context is taken into account by dividing up the OVIS corpus into context-dependent subcorpora. Each system question triggers a subcorpus by which the user answer is analysed and interpreted. Our experiments indicate that the context-sensitive DOP model obtains better accuracy than the original model, allowing for fast and robust processing of spoken input.