Generic epsilon -Removal Algorithm for Weighted Automata
CIAA '00 Revised Papers from the 5th International Conference on Implementation and Application of Automata
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Correcting ESL errors using phrasal SMT techniques
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Latent-variable modeling of string transductions with finite-state methods
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Meteor: an automatic metric for MT evaluation with high levels of correlation with human judgments
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
OpenFst: a general and efficient weighted finite-state transducer library
CIAA'07 Proceedings of the 12th international conference on Implementation and application of automata
Hitting the right paraphrases in good time
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Automated whole sentence grammar correction using a noisy channel model
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Correction detection and error type selection as an ESL educational aid
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Hi-index | 0.00 |
We present a novel noisy channel model for correcting text produced by English as a second language (ESL) authors. We model the English word choices made by ESL authors as a random walk across an undirected bipartite dictionary graph composed of edges between English words and associated words in an author's native language. We present two such models, using cascades of weighted finite-state transducers (wFSTs) to model language model priors, random walk-induced noise, and observed sentences, and expectation maximization (EM) to learn model parameters after Park and Levy (2011). We show that such models can make intelligent word substitutions to improve grammaticality in an unsupervised setting.