[PDF] Top 20 Joint Learning and Inference for Grammatical Error Correction
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Joint Learning and Inference for Grammatical Error Correction
... two joint approaches: (1) a joint infer- ence approach implemented on top of individually learned models using an integer linear programming formulation (ILP, (Roth and Yih, 2004)), and (2) a model that ... See full document
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Fluency Boost Learning and Inference for Neural Grammatical Error Correction
... for grammatical error correction (GEC) have two limitations: (1) a seq2seq model may not be well gen- eralized with only limited error-corrected data; (2) a seq2seq model may fail to ... See full document
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A Beam Search Decoder for Grammatical Error Correction
... word used by the writer and the classifier is suffi- ciently confident in its prediction, the observed word is replaced by the prediction. Although considerable progress has been made, the classification approach suffers ... See full document
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Adapting Grammatical Error Correction Based on the Native Language of Writers with Neural Network Joint Models
... predicting error distributions in ESL data (Berzak et ...specific error types using the classification ...the error fre- quency in L1-specific text to improve ...article correction, by ... See full document
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Grammatical Error Correction: Machine Translation and Classifiers
... to grammatical error correc- tion – machine learning classification and machine ...two learning frame- works and through error analysis of the output of the state-of-the-art systems, we ... See full document
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A Hybrid Model For Grammatical Error Correction
... A pre-processing and a post-processing filter are utilized which include filters for some idio- matic phrases extracted from the training dataset. The Frequent Pattern Growth Algorithm (FP- Growth) is widely used for ... See full document
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The BEA 2019 Shared Task on Grammatical Error Correction
... on Grammatical Error Correc- tion (GEC) continues the tradition of the previ- ous Helping Our Own (HOO) and Conference on Natural Language Learning (CoNLL) shared tasks (Dale and Kilgarriff, 2011; ... See full document
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The CUED’s Grammatical Error Correction Systems for BEA 2019
... on grammatical error correction with submissions to the low-resource and the restricted ...a joint submission with the Cambridge Univer- sity Computer Lab (Yuan et ... See full document
8
Better Evaluation for Grammatical Error Correction
... time. Grammatical error correction is an important NLP task with useful applications for second lan- guage ...for error correction is typically done by computing F 1 measure ... See full document
5
Grammatical Error Correction with Alternating Structure Optimization
... on grammatical error correc- tion was done by Knight and Chander (1994) on arti- cle ...memory-based learning (Minnen et al., 2000), decision tree learning (Nagata et ... See full document
9
Grammatical Error Correction with Neural Reinforcement Learning
... reinforcement learning. In reinforcement learning, agents aim to maximize expected rewards by taking actions and updating the policy under a given ... See full document
7
A Meta Learning Approach to Grammatical Error Correction
... In this paper, we present a novel approach to the GEC task using meta-learning. We focus mainly on article errors for two reasons. First, articles are one of the most significant sources of GE for the learners ... See full document
5
Grammatical Error Correction Using Feature Selection and Confidence Tuning
... necessary use of articles. For example, in the fol- lowing sentence“Over these years, it had helped humans to improve the accessibility in the forms of cards to gain access to certain places.”there are two thes in which ... See full document
5
System Combination for Grammatical Error Correction
... of error-annotated learner (“par- allel”) ...social learning platform Lang-8 and built an SMT system for correcting grammatical errors in ...all error types are dealt ... See full document
12
Generating artificial errors for grammatical error correction
... Building error correction systems using machine learning techniques can require a considerable amount of annotated data which is difficult to ob- ...Available error-annotated corpora are often ... See full document
11
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
11
A Tree Transducer Model for Grammatical Error Correction
... five error types: Article or determiner, preposition, noun number, verb form, and subject-verb agreement ...other error types are also included in the error ...other error types to the correct ... See full document
9
Grammatical Error Correction Considering Multi word Expressions
... matical error correction is targeted on one or few restricted types of learners’ ...of grammatical errors (Mizu- moto et ...errors, grammatical error correction methods using ... See full document
5
Noisy Channel for Low Resource Grammatical Error Correction
... Grammatical Error Correction Grammatical Error Correction (GEC) is the task of automat- ically correcting grammatical errors in written ... See full document
6
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
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