Results 41 to 50 of about 2,197,203 (280)

GenERRate: generating errors for use in grammatical error detection [PDF]

open access: yes, 2009
This paper explores the issue of automatically generated ungrammatical data and its use in error detection, with a focus on the task of classifying a sentence as grammatical or ungrammatical.
Foster, Jennifer, Andersen, Øistein E.
core   +2 more sources

Identification and Correction of Grammatical Errors in Ukrainian Texts Based on Machine Learning Technology

open access: yesMathematics, 2023
A machine learning model for correcting errors in Ukrainian texts has been developed. It was established that the neural network has the ability to correct simple sentences written in Ukrainian; however, the development of a full-fledged system requires ...
Vasyl Lytvyn   +4 more
doaj   +1 more source

Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction [PDF]

open access: yesProceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2017
Until now, error type performance for Grammatical Error Correction (GEC) systems could only be measured in terms of recall because system output is not annotated. To overcome this problem, we introduce ERRANT, a grammatical ERRor ANnotation Toolkit designed to automatically extract edits from parallel original and corrected sentences and classify them ...
Christopher Bryant 0001   +2 more
openaire   +2 more sources

Research progress on Chinese and English text error correction [PDF]

open access: yesITM Web of Conferences
Text error correction is an essential task in natural language processing (NLP) that focuses on automatically identifying and correcting errors in written text. With the increasing amount of digital text in both Chinese and English, errors such as typos,
Wang Yao
doaj   +1 more source

EliaGorokhovsky/Time-Error-Correction-MATLAB: v1.0.0

open access: yes, 2022
Added code, data, and figures. Full Changelog: https://github.com/EliaGorokhovsky/Time-Error-Correction-MATLAB/commits/v1.0.
Elia Gorokhovsky
core   +1 more source

Nonlinear error correction, asymmetric adjusment and cointegration [PDF]

open access: yes, 1991
This paper has three main components. First, it outlines a model of nonlinear error correction (NEC) in which the linear error correction term a'Xt (the vector time series Xt is cointegrated, a is the cointegrating vector) is replaced by the nonlinear ...
Pfann, Gerard, Escribano, Álvaro
core   +1 more source

Czech Grammar Error Correction with a Large and Diverse Corpus

open access: yesTransactions of the Association for Computational Linguistics, 2022
We introduce a large and diverse Czech corpus annotated for grammatical error correction (GEC) with the aim to contribute to the still scarce data resources in this domain for languages other than English.
Jakub Náplava   +3 more
doaj   +1 more source

Extending Quantum Error Correction: New Continuous Measurement Protocols and Improved Fault-Tolerant Overhead [PDF]

open access: yes, 2004
Quantum mechanical applications range from quantum computers to quantum key distribution to teleportation. In these applications, quantum error correction is extremely important for protecting quantum states against decoherence.
Ahn, Charlene Sonja
core   +1 more source

A Crash Course in Automatic Grammatical Error Correction [PDF]

open access: yesProceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts, 2020
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting all types of errors in written text. Although most research has focused on correcting errors in the context of English as a Second Language (ESL), GEC can also be applied to other languages and native text.
Roman Grundkiewicz   +2 more
openaire   +1 more source

Erroneous data generation for Grammatical Error Correction [PDF]

open access: yesProceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, 2019
It has been demonstrated that the utilization of a monolingual corpus in neural Grammatical Error Correction (GEC) systems can significantly improve the system performance. The previous state-of-the-art neural GEC system is an ensemble of four Transformer models pretrained on a large amount of Wikipedia Edits. The Singsound GEC system follows a similar
Shuyao Xu   +3 more
openaire   +2 more sources

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