[PDF] Top 20 Corpora Generation for Grammatical Error Correction
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Corpora Generation for Grammatical Error Correction
... 2010), (Felice et al., 2014; Xie et al., 2016; Rei et al., 2017) has investigated multiple strategies for generating artificial errors in GEC. Cahill et al. (2013) show that preposition corrections extracted from ... See full document
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The BEA 2019 Shared Task on Grammatical Error Correction
... With this in mind, another significant contribu- tion of the BEA-2019 shared task is the introduc- tion of a new annotated dataset, the Cambridge English Write & Improve (W&I) and LOCNESS corpus, which is ... See full document
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Automatic Grammatical Error Correction for Sequence to sequence Text Generation: An Empirical Study
... Table 6 shows the results for the effects of GEC on sentence compression and simplification. For sentence compression, BLEU decreases from 60.38 to 58.77 after GEC post editing. We man- ually analyze the results and find ... See full document
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Cross Corpora Evaluation and Analysis of Grammatical Error Correction Models — Is Single Corpus Evaluation Enough?
... Grammatical error correction (GEC) is the task of correcting various grammatical errors in a given text, which is typically written by non-native ... See full document
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Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
... Having extracted the edits, the next step is to as- sign them error types. While Swanson and Ya- mangil (2012) did this by means of maximum entropy classifiers, one disadvantage of this ap- proach is that such ... See full document
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A Meta Learning Approach to Grammatical Error Correction
... article error correction are already well engineered allowing for quick analysis of the ...learner corpora, rather than just one GE tagged ...article error correction ... See full document
5
Automatic Metric Validation for Grammatical Error Correction
... text generation tasks (Sennrich et ...the correction with the reference and penalizes unchanged n-grams in the correction that are changed in the ... See full document
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Grammatical Error Correction with Alternating Structure Optimization
... In this work, we aim to overcome both problems. First, we present a novel approach to GEC based on Alternating Structure Optimization (ASO) (Ando and Zhang, 2005). Our approach is able to train models on annotated ... See full document
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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
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Grammatical Error Correction in Low Resource Scenarios
... Other corpora are corrected by trained annota- tors making them much cleaner but also signifi- cantly smaller. NUCLE (Dahlmeier et al., 2013) has 57 151 sentences originating from 1 400 es- says written by mainly ... See full document
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Generating artificial errors for grammatical error correction
... correct grammatical errors and context- sensitive spelling mistakes in English and ...Training corpora are obtained by injecting arti- ficial errors into well-formed treebank sentences using predefined ... See full document
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Erroneous data generation for Grammatical Error Correction
... In this section, we describe our error generating method. For each sentence, we assign a proba- bility distribution (as shown in Table 4) to deter- mine the number of errors according to the sen- tence length. The ... See full document
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Neural and FST based approaches to grammatical error correction
... Artificial error generation is the process of in- jecting artificial errors into a set of error-free sen- ...ual error annotation of learner data is a slow and expensive process, artificial ... See full document
12
Cross Sentence Grammatical Error Correction
... Similar to most published GEC models (Chol- lampatt and Ng, 2018b; Junczys-Dowmunt et al., 2018; Grundkiewicz and Junczys-Dowmunt, 2018), we rely on two datasets for training: Lang-8 Learner Corpora 3 v2.0 ... See full document
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Improving Precision of Grammatical Error Correction with a Cheat Sheet
... Artificial Error Generation has been a long-studied technique for creating more training data for Grammatical Error Correction ...artificial error, one making use of the real ... See full document
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Minimally Augmented Grammatical Error Correction
... cal error correction. We introduce Minimally- Augmented Grammatical Error Correction (MAGEC) that does not require any error- labelled ...ror generation method based on ... See full document
7
The CUED’s Grammatical Error Correction Systems for BEA 2019
... In-domain corpus over-sampling The BEA- 2019 training corpora (Tab. 5) differ significantly not only in size but also their closeness to the target domain. The W&I+LOCNESS corpus is most similar to the ... See full document
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System Combination for Grammatical Error Correction
... work was done by Brockett et al. (2006), where they used SMT to correct mass noun errors. The major impediment in using the SMT approach for GEC is the lack of error-annotated learner (“par- allel”) ... See full document
12
Human Evaluation of Grammatical Error Correction Systems
... automatic grammatical error correction (GEC) sys- ...for grammatical error correction in terms of correlation with human ... See full document
10
Joint Learning and Inference for Grammatical Error Correction
... ESL error cor- rection has addressed the task by building statistical models that specialize in correcting a specific type of a ...agreement error on the verb “have” interacts with the noun number ... See full document
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