[PDF] Top 20 Grammatical Error Correction: Machine Translation and Classifiers
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Grammatical Error Correction: Machine Translation and Classifiers
... approach, error con- fusions are learned automatically via the phrase translation tables extracted from the parallel train- ing ...phrase-level correction that includes both a prepo- sition ... See full document
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Discriminative Reranking for Grammatical Error Correction with Statistical Machine Translation
... Heafield et al. (2009) proposed a system combi- nation method for machine translation that is sim- ilar to that of reranking. System combination is a method that merges the outputs of multiple systems to ... See full document
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Factored Statistical Machine Translation for Grammatical Error Correction
... on grammatical error correction ...possible error types in a real-life environment, we propose a factored statistical machine translation (SMT) model for this ...consider ... See full document
8
Constrained Grammatical Error Correction using Statistical Machine Translation
... Nitin Madnani, Joel Tetreault, and Martin Chodorow. 2012. Exploring grammatical error correction with not-so-crummy machine translation. In Proceedings of the Seventh Workshop on ... See full document
10
Approaching Neural Grammatical Error Correction as a Low Resource Machine Translation Task
... neural machine translation and has been demonstrated to be generally superior to UNK-replacement ...of grammatical error correction even when word segmentation issues have been explored ... See full document
12
Systematically Adapting Machine Translation for Grammatical Error Correction
... to grammatical error correc- tion developed rule-based systems or classifiers targeting specific error types such as prepositions or determiners, ...in machine translation, ... See full document
12
The AMU System in the CoNLL 2014 Shared Task: Grammatical Error Correction by Data Intensive and Feature Rich Statistical Machine Translation
... out-of-the-box machine translation toolk- its like Moses (Koehn et ...cal error correction seems ...grammar correction system, the standard features and opti- mization methods are ... See full document
9
Grammatical error correction using neural machine translation
... Grammatical error correction (GEC) is the task of detecting and correcting grammatical errors in text written by non-native English ...building machine learning classifiers for ... See full document
7
Phrase based Machine Translation is State of the Art for Automatic Grammatical Error Correction
... We have shown that a pure SMT system actu- ally outperforms the best reported results for any paradigm in GEC if correct parameter tuning is per- formed. With this tuning mechanism available, task- specific features have ... See full document
11
Near Human Level Performance in Grammatical Error Correction with Hybrid Machine Translation
... statistical machine trans- lation (Rozovskaya and Roth, 2016; Junczys- Dowmunt and Grundkiewicz, 2016; Chollampatt and Ng, ...chine translation (Yuan and Briscoe, 2016; Xie et ... See full document
7
Improving Chinese Grammatical Error Correction with Corpus Augmentation and Hierarchical Phrase based Statistical Machine Translation
... Chinese grammatical error diagnosis (CGED). We use a statistical machine translation method already ap- plied to several similar tasks (Brockett et ...alternative translation models ... See full document
6
Exploring Grammatical Error Correction with Not So Crummy Machine Translation
... To date, most work in grammatical error cor- rection has focused on targeting specific er- ror types. We present a probe study into whether we can use round-trip translations ob- tained from Google ... See full document
10
Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
... entropy classifiers, one disadvantage of this ap- proach is that such classifiers are biased towards their particular training ...dataset-agnostic error type classifier is much more ... See full document
13
A Meta Learning Approach to Grammatical Error Correction
... to grammatical error correction by building a meta-classifier using multiple GE tagged corpora with different characteristics in various ...base classifiers are ... See full document
5
Corpora Generation for Grammatical Error Correction
... the Grammatical Error Correc- tion (GEC) task can be credited to approaching the problem as a translation task (Brockett et ...a grammatical target language. This has enabled Neural ... See full document
11
System Combination for Grammatical Error Correction
... common grammatical mistakes made by ESL learners, such as article and prepo- sition errors (Han et ...tical classifiers are trained either from learner or non-learner ...the error type ... See full document
12
Grammatical Error Correction with Alternating Structure Optimization
... on grammatical error correc- tion was done by Knight and Chander (1994) on arti- cle ...different classifiers, including memory-based learning (Minnen et ... See full document
9
Grammatical Error Correction with Neural Reinforcement Learning
... predicted word sequence (ˆ y 1 t−1 ) at test time. Namely, the model is not exposed to the predicted words in training time. This is problematic, be- cause once the model fails to predict a correct word at test time, it ... See full document
7
Ground Truth for Grammatical Error Correction Metrics
... tasks, grammatical error correction metrics must be evaluated against ground ...a grammatical correction, together with the fact that the use case for grammatically-corrected output is ... See full document
6
Memory based Grammatical Error Correction
... It is important to note that not just one classifi- cation is returned for a given context by the IGTree classifier, but a distribution of results and their re- spective occurrence counts. The classifier matches the ... See full document
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