[PDF] Top 20 Human Evaluation of Grammatical Error Correction Systems
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Human Evaluation of Grammatical Error Correction Systems
... The final human-created ranking (Table 3b) con- sists of four non-overlapping rank clusters. Rank ranges have been calculated at a confidence level of 95%. Comparing the official CoNLL-2014 ranking (Table 3a) with ... See full document
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Neural Grammatical Error Correction Systems with Unsupervised Pre training on Synthetic Data
... a error- annotated corpus as a seed to generate artificial errors reflecting linguistic properties and error dis- tributions observed in natural-error corpora (Foster and Andersen, 2009; Felice and ... 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 ... See full document
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Automatic Metric Validation for Grammatical Error Correction
... of evaluation by human rankings due to its unreli- ability (Graham et ...that human rankings in GEC also suffer from low inter-rater agreement, motivating the development of alternative ... See full document
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Erroneous data generation for Grammatical Error Correction
... top systems in the BEA 2019 GEC Shared ...of-the-art systems on the CoNLL-2014 (Ng et ...reaches human- level performance on the JFLEG (Napoles et ... See full document
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There’s No Comparison: Reference less Evaluation Metrics in Grammatical Error Correction
... evaluating grammatical error correction (GEC) systems rely on gold-standard ...with human judgments and are competitive with the leading reference-based evaluation ... See full document
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Ground Truth for Grammatical Error Correction Metrics
... which grammatical error correction (GEC) system is best? A num- ber of metrics have been proposed over the years, each motivated by weaknesses of previous metrics; however, the metrics themselves ... See full document
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Grammatical Induction with Error Correction for Deterministic Context-free L-systems
... D0L-system. The simplest class of L-systems are called D0L-system (deterministic context-free L-system). D0L- system is defined as G = (V, C, ω, P ), where V and C denote sets of variables and constants, ω is an ... See full document
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System Combination for Grammatical Error Correction
... various error types and then merges the ...of systems to combine the outputs of their rule based system and their SMT ...those systems are different from our approach, because they combine individual ... See full document
12
Generating artificial errors for grammatical error correction
... their systems on sentences that have no spelling mistakes so as to avoid degrading per- ...of error types (mainly articles and preposi- tions) which are closed word classes and therefore have reduced ... See full document
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Near Human Level Performance in Grammatical Error Correction with Hybrid Machine Translation
... NMT systems produce different ...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
Joint Learning and Inference for Grammatical Error Correction
... The approach of addressing each type of mistake in- dividually is problematic when multiple phenomena interact. Consider the examples in Table 3 and the predictions made by the Illinois system. In the first and second ... See full document
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Grammatical Error Correction in Low Resource Scenarios
... We provide comparison between our model and existing systems on W&I+L test and development sets and on CoNLL 14 test set in Table 5. Even if the results on the W&I+L development set are only partially ... See full document
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Grammatical Error Correction with Neural Reinforcement Learning
... a human evaluation using Amazon Mechani- cal Turk ...five systems randomly selected from all eight: the four baseline models, MLE, NRL, one randomly selected human correction, and the ... See full document
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Grammatical Error Correction with Alternating Structure Optimization
... to grammatical error correction based on Alternating Struc- ture ...sive evaluation for article and preposition er- rors using various feature ... See full document
9
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 ...automatic evaluation metric would be needed as ... See full document
5
Minimally Augmented Grammatical Error Correction
... other error types; with the complement errors corrected (Table 6). Our systems indeed perform best on misspellings and punctuation errors, but are capable of correcting various error ... See full document
7
Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
... concerning error scheme design is that it is always possible to add new categories for increasingly detailed error types; for instance, we currently label [could → should] a tense error, when it ... See full document
13
Connecting the Dots: Towards Human Level Grammatical Error Correction
... GEC has gained popularity since the CoNLL-2014 (Ng et al., 2014) shared task was organized. Un- like previous shared tasks (Dale and Kilgarriff, 2011; Dale et al., 2012; Ng et al., 2013) that fo- cused only on a few ... See full document
7
Grammatical error correction using hybrid systems and type filtering
... As described in Section 2.5, we can evaluate per- formance by error type in order to identify and re- move unnecessary corrections. In particular, we tried to optimise our best hybrid system (#6) by filtering out ... See full document
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