Grammatical Error Detection

17 papers with code • 4 benchmarks • 4 datasets

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.

Latest papers with no code

Approximate Conditional Coverage & Calibration via Neural Model Approximations

no code yet • 28 May 2022

A typical desideratum for quantifying the uncertainty from a classification model as a prediction set is class-conditional singleton set calibration.

A Warm Start and a Clean Crawled Corpus -- A Recipe for Good Language Models

no code yet • 14 Jan 2022

To train the models we introduce a new corpus of Icelandic text, the Icelandic Common Crawl Corpus (IC3), a collection of high quality texts found online by targeting the Icelandic top-level-domain (TLD).

Exploring the Capacity of a Large-scale Masked Language Model to Recognize Grammatical Errors

no code yet • Findings (ACL) 2022

In this paper, we explore the capacity of a language model-based method for grammatical error detection in detail.

Combining GCN and Transformer for Chinese Grammatical Error Detection

no code yet • 19 May 2021

This paper describes our system at NLPTEA-2020 Task: Chinese Grammatical Error Diagnosis (CGED).

Grammatical error detection in transcriptions of spoken English

no code yet • COLING 2020

We describe the collection of transcription corrections and grammatical error annotations for the CrowdED Corpus of spoken English monologues on business topics.

LinggleWrite: a Coaching System for Essay Writing

no code yet • ACL 2020

This paper presents LinggleWrite, a writing coach that provides writing suggestions, assesses writing proficiency levels, detects grammatical errors, and offers corrective feedback in response to user{'}s essay.

Neural Models for Predicting Celtic Mutations

no code yet • LREC 2020

The Celtic languages share a common linguistic phenomenon known as initial mutations; these consist of pronunciation and spelling changes that occur at the beginning of some words, triggered in certain semantic or syntactic contexts.

Automated Writing Support Using Deep Linguistic Parsers

no code yet • LREC 2020

This paper introduces a new web system that integrates English Grammatical Error Detection (GED) and course-specific stylistic guidelines to automatically review and provide feedback on student assignments.

The AIP-Tohoku System at the BEA-2019 Shared Task

no code yet • WS 2019

We introduce the AIP-Tohoku grammatical error correction (GEC) system for the BEA-2019 shared task in Track 1 (Restricted Track) and Track 2 (Unrestricted Track) using the same system architecture.

Grammatical-Error-Aware Incorrect Example Retrieval System for Learners of Japanese as a Second Language

no code yet • WS 2019

Existing example retrieval systems do not include grammatically incorrect examples or present only a few examples, if any.