[PDF] Top 20 Grammatical Error Correction in Low Resource Scenarios
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Grammatical Error Correction in Low Resource Scenarios
... Grammatical error correction in English is a long studied problem with many existing systems and ...on error correction of other ...on grammatical error correction ... See full document
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The BEA 2019 Shared Task on Grammatical Error Correction
... and Low Resource ...The Low Resource track, in contrast, significantly lim- its the amount of annotated data available to par- ticipants and encourages development of systems that do not rely ... See full document
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The CUED’s Grammatical Error Correction Systems for BEA 2019
... on grammatical er- ror correction. Our submission to the low- resource track is based on prior work on us- ing finite state transducers together with strong neural language ... See full document
8
Minimally Augmented Grammatical Error Correction
... in low- resource approaches to automatic grammati- cal error ...Augmented Grammatical Error Correction (MAGEC) that does not require any error- labelled ...In ... See full document
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Grammatical Error Correction Considering Multi word Expressions
... to low. The correction performance of articles and prepositions that are likely to become a component word of MWEs is considered to improve by this ... 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 ...for low-resource tasks (Koehn and ... See full document
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A Hybrid Model For Grammatical Error Correction
... interacting error corrections were considered originally but dropped at last because of the bad effects brought about by them such as the accumulation of errors which lead to a very low ... See full document
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RACAI GEC – A hybrid approach to Grammatical Error Correction
... Grammatical error correction (GEC) is a com- plex task mainly because of the natural depend- encies between the words of a sentence both at the lexical and the semantic levels, leave it aside the ... See full document
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Joint Learning and Inference for Grammatical Error Correction
... fol- low the popular approach to ESL error correction borrowed from the context-sensitive spelling correc- tion task (Golding and Roth, 1999; Carlson et ... See full document
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Automatic Metric Validation for Grammatical Error Correction
... Table 1 shows CHR with Spearman ρ (Pear- son r shows similar trends). Results on the two datasets diverge considerably, despite their use of the same systems and corpus (albeit a different sub-set thereof). For example, ... See full document
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Grammatical Error Correction: Machine Translation and Classifiers
... to grammatical error correc- tion – machine learning classification and machine ...through error analysis of the output of the state-of-the-art systems, we identify key strengths and weaknesses of ... See full document
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A Meta Learning Approach to Grammatical Error Correction
... Although the proposed model introduced a tradeoff between precision and recall (Rec.), this tradeoff was tolerable in order to improve the overall F1-score. Since GEC is a task where false alarm is critical, obtaining ... See full document
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A Tree Transducer Model for Grammatical Error Correction
... annotated errors is much higher in the test set than in the development set: 46% of clauses have cor- rections. It has been found previously that a low frequency of errors increase the difficulty of the ... See full document
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Grammatical Error Correction with Neural Reinforcement Learning
... Results Table 3 shows the human evaluation by TrueSkill and automated metric (GLEU). In both dev and test set, NRL outperforms MLE and other baselines in both the human and automatic evalua- tions. Human evaluation and ... See full document
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Noisy Channel for Low Resource Grammatical Error Correction
... the low-resource track of the BEA 2019 shared task on Grammatical Error Correction ...specific error types and 2) OpenAI’s GPT-2 model, utilizing that it can operate with ... See full document
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Using Wikipedia Edits in Low Resource Grammatical Error Correction
... ERRANT, the ERRor ANnotation Tool (Felice et al., 2016; Bryant et al., 2017), analyzes pairs of English sentences from a GEC corpus to iden- tify the types of corrections performed. The to- kens in a pair of ... See full document
6
Approaching Neural Grammatical Error Correction as a Low Resource Machine Translation Task
... in grammatical er- ror correction (GEC) did not reach state-of- the-art results compared to phrase-based sta- tistical machine translation (SMT) ...and low-resource neural MT and successfully ... See full document
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Human Evaluation of Grammatical Error Correction Systems
... automatic grammatical error correc- tion (GEC) has seen a number of shared tasks of different scope and for different ...on Grammatical Error Correction for ESL (English as a second ... See full document
10
Generating artificial errors for grammatical error correction
... correct grammatical errors and context- sensitive spelling mistakes in English and ...one error template, thereby generating many pairs for the same original ... See full document
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A Beam Search Decoder for Grammatical Error Correction
... specific error categories, such as articles and prepo- ...of error-annotated ...on grammatical error correction (Dale and Kilgarriff, ... See full document
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