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Grammatical Error Detection

Grammatical Error Detection (GED) is the task of detecting different kinds of errors in text such as spelling, punctuation, grammatical, and word choice errors. Grammatical error detection (GED) is one of the key component in grammatical error correction (GEC) community.

Papers

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Showing 51–75 of 100 papers

TitleStatusHype
Detection of Chinese Word Usage Errors for Non-Native Chinese Learners with Bidirectional LSTM—0
The Construction of a Chinese Collocational Knowledge Resource and Its Application for Second Language Acquisition—0
Chinese Grammatical Error Diagnosis Using Single Word Embedding—0
Bi-LSTM Neural Networks for Chinese Grammatical Error Diagnosis—0
Word Order Sensitive Embedding Features/Conditional Random Field-based Chinese Grammatical Error Detection—0
Automatic Grammatical Error Detection for Chinese based on Conditional Random Field—0
Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs—0
Grammatical Error Detection Based on Machine Learning for Mandarin as Second Language Learning—0
Exploiting Unlabeled Data for Neural Grammatical Error Detection—0
Attending to Characters in Neural Sequence Labeling Models—0
Compositional Sequence Labeling Models for Error Detection in Learner Writing—0
Shallow Semantic Reasoning from an Incomplete Gold Standard for Learner Language—0
UW-Stanford System Description for AESW 2016 Shared Task on Grammatical Error Detection—0
The NTNU-YZU System in the AESW Shared Task: Automated Evaluation of Scientific Writing Using a Convolutional Neural Network—0
Model Combination for Correcting Preposition Selection Errors—0
A Report on the Automatic Evaluation of Scientific Writing Shared Task—0
Detecting Word Usage Errors in Chinese Sentences for Learning Chinese as a Foreign Language—0
Addressing Class Imbalance in Grammatical Error Detection with Evaluation Metric Optimization—0
A Light Rule-based Approach to English Subject-Verb Agreement Errors on the Third Person Singular Forms—0
Can Natural Language Processing Become Natural Language Coaching?—0
Chinese Grammatical Error Diagnosis Using Ensemble Learning—0
Condition Random Fields-based Grammatical Error Detection for Chinese as Second Language—0
Overview of the NLP-TEA 2015 Shared Task for Chinese Grammatical Error Diagnosis—0
WriteAhead2: Mining Lexical Grammar Patterns for Assisted Writing—0
Automated Evaluation of Scientific Writing: AESW Shared Task Proposal—0
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