Attention, intentions, and the structure of discourse
Computational Linguistics
A Rational Design for a Weighted Finite-State Transducer Library
WIA '97 Revised Papers from the Second International Workshop on Implementing Automata
A collaborative planning model of intentional structure
Computational Linguistics
Lucene in Action (In Action series)
Lucene in Action (In Action series)
Generalized algorithms for constructing statistical language models
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Learning the structure of task-driven human-human dialogs
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Discriminative classifiers for deterministic dependency parsing
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A best-first probabilistic shift-reduce parser
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Incremental parsing models for dialog task structure
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Qme!: a speech-based question-answering system on mobile devices
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Finite-state models for speech-based search on mobile devices
Natural Language Engineering
Learning the Structure of Task-Driven Human–Human Dialogs
IEEE Transactions on Audio, Speech, and Language Processing
Automatic pipeline construction for real-time annotation
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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Natural Language Processing systems are often composed of a sequence of transductive components that transform their input into an output with additional syntactic and/or semantic labels. However, each component in this chain is typically error-prone and the error is magnified as the processing proceeds down the chain. In this paper, we present details of two systems, first, a speech driven question answering system and second, a dialog modeling system, both of which reflect the theme of tightly incorporating constraints across multiple components to improve the accuracy of their tasks.