[PDF] Top 20 Factored Statistical Machine Translation for Grammatical Error Correction
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Factored Statistical Machine Translation for Grammatical Error Correction
... phrase-based translation models, factored models make use of additional linguistic clues to guide the system such that it generates translated sentences in which morphological and syntactic constraints are ... See full document
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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
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Exploring Grammatical Error Correction with Not So Crummy Machine Translation
... grammar correction; they learn a noise model from a dataset of errorful sen- tences but do not rely on ...round-trip translation for such sentences via a single pivot language ...round-trip ... See full document
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Approaching Neural Grammatical Error Correction as a Low Resource Machine Translation Task
... Junczys-Dowmunt and Grundkiewicz (2016) no- ticed that when tuning on the entire NUCLE cor- pus, even better results can be achieved if the error rate of NUCLE is adapted to the error rate of the original ... See full document
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Phrase based Machine Translation is State of the Art for Automatic Grammatical Error Correction
... for translation-focused settings: usually they consist of between 2000 and 3000 sentences, they should be a good representation of the testing data, sparse features require more sentences or more references, ...a ... See full document
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Near Human Level Performance in Grammatical Error Correction with Hybrid Machine Translation
... the statistical and neural ...unique correction (is change → has changed), but it fails in generating some corrections from the neural system, ...local correction made by the SMT system (is ... See full document
7
Improving Grammatical Error Correction via Pre Training a Copy Augmented Architecture with Unlabeled Data
... Neural machine translation systems have be- come state-of-the-art approaches for Gram- matical Error Correction (GEC) task. In this paper, we propose a copy-augmented archi- tecture for the ... See full document
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Connecting the Dots: Towards Human Level Grammatical Error Correction
... few error types, the CoNLL-2014 shared task dealt with correction of all kinds of textual ...Neural machine translation ap- proaches have also showed some promise (Xie et ... See full document
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Grammatical Machine Translation
... multi-word translation units from phrase- based SMT into a transfer system for dependency structure ...The statistical components of our system are modeled on the phrase-based sys- tem of Koehn et ... See full document
8
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
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Grammatical Error Correction: Machine Translation and Classifiers
... specific error type. Because an error type needs to be de- fined, typically only well-defined mistakes can be addressed in a straightforward ...an error type, a confusion set is specified and ... See full document
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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
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Discriminative Reranking for Grammatical Error Correction with Statistical Machine Translation
... on grammatical error correction has received considerable ...errors, grammatical error cor- rection methods that employ statistical ma- chine translation (SMT) have been ... See full document
6
Grammatical error correction using neural machine translation
... level translation model to translate those words in a post-processing ...of error cor- rection ...level translation model for translating the source words that are responsible for the target unknown ... See full document
7
Systematically Adapting Machine Translation for Grammatical Error Correction
... of error-coded ...be error coded, and humans perceive sentences corrected with fluency edits to be more grammatical than those corrected with error-coded edits alone (Sakaguchi et ... See full document
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Improving Chinese Grammatical Error Correction with Corpus Augmentation and Hierarchical Phrase based Statistical Machine Translation
... stead of F1. In other words, we expected our sys- tem to have high accuracy because, as Ng et al. say in CoNLL-2014, “it is important for a gram- mar checker that its proposed corrections are highly accurate in order to ... See full document
6
Minimally Augmented Grammatical Error Correction
... To counter the argument that – mostly due to the introduced character-level noise and strong lan- guage modelling – MAGEC can only correct these “simple” errors, we evaluate it against test sets that contain either ... See full document
7
Better Evaluation for Grammatical Error Correction
... In this work, we propose a method, called Max- Match (M 2 ), to overcome this problem. The key idea is that if there are multiple possible ways to arrive at the same correction, the system should be eval- uated ... See full document
5
System Combination for Grammatical Error Correction
... various error types and then merges the ...of grammatical error correction, our work is novel as it is the first that uses system combination to improve grammatical error ... See full document
12
Word Representations in Factored Neural Machine Translation
... ral machine translation ...for translation from English into two mor- phologically rich languages, Czech and Latvian, and show the importance of ex- plicitly modeling target ... See full document
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