Building probabilistic models for natural language
Building probabilistic models for natural language
Statistical methods for speech recognition
Statistical methods for speech recognition
Probabilistic top-down parsing and language modeling
Computational Linguistics
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
A simple approach to building ensembles of Naive Bayesian classifiers for word sense disambiguation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Classifier combination for improved lexical disambiguation
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Tagging inflective languages: prediction of morphological categories for a rich, structured tagset
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
A second-order Hidden Markov Model for part-of-speech tagging
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Serial combination of rules and statistics: a case study in Czech tagging
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
HLT '93 Proceedings of the workshop on Human Language Technology
The dawn of statistical asr and mt
Computational Linguistics
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The state of the art methods of disambiguation in automatic text processing are considered. Special attention is paid to smoothed probabilistic N-gram models.