Speech understanding and dialouge over the telephone: an overview of the ESPRIT SUNDIAL
HLT '91 Proceedings of the workshop on Speech and Natural Language
Evaluation of spoken language systems: the ATIS domain
HLT '90 Proceedings of the workshop on Speech and Natural Language
The CMU air travel information service: understanding spontaneous speech
HLT '90 Proceedings of the workshop on Speech and Natural Language
TINA: a natural language system for spoken language applications
Computational Linguistics
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
Automatic labeling of semantic roles
Computational Linguistics
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Incorporating Prior Knowledge into Boosting
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Machine Learning for Sequential Data: A Review
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Hidden Understanding Models for Statistical Sentence Understanding
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Table extraction using conditional random fields
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Gemini: a natural language system for spoken-language understanding
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Named entity recognition: a maximum entropy approach using global information
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Shallow parsing with conditional random fields
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Collective information extraction with relational Markov networks
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Exploiting non-local features for spoken language understanding
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Efficiently inducing features of conditional random fields
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Minimum tag error for discriminative training of conditional random fields
Information Sciences: an International Journal
Hybrid semantic analysis system - ATIS data evaluation
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
SWSNL: Semantic Web Search Using Natural Language
Expert Systems with Applications: An International Journal
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Spoken language understanding (SLU) addresses the problem of mapping natural language speech to frame structure encoding of its meaning. The statistical sequential labeling method has been successfully applied to SLU tasks; however, most sequential labeling approaches lack long-distance dependency information handling method. In this paper, we exploit non-local features as an estimate of long-distance dependencies to improve performance of the statistical SLU problem. A method we propose is to use trigger pairs automatically extracted by a feature induction algorithm. We describe a light practical version of the feature inducer for which a simple modification is efficient and successful. We evaluate our method on three SLU tasks and show an improvement of performance over the baseline local model.