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Jorge Luis Borges' Medieval Aesthetics of Failure

Critical Quarterly, EarlyView.
Irina Dumitrescu
wiley   +1 more source

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Efficient Grammatical Error Correction with Hierarchical Error Detections and Correction

2021 IEEE International Conference on Web Services (ICWS), 2021
Noisy text is common in semantic services and can have bad effects. Grammatical Error Correction (GEC) can be used to improve text quality, but traditional neural machine translation approaches need hundreds of milliseconds to correct a single text, which is unacceptable to time-sensitive services.
Fayu Pan, Bin Cao
openaire   +1 more source

The BEA-2019 Shared Task on Grammatical Error Correction

BEA@ACL, 2019
This paper reports on the BEA-2019 Shared Task on Grammatical Error Correction (GEC). As with the CoNLL-2014 shared task, participants are required to correct all types of errors in test data.
Christopher Bryant, Mariano Felice, Øistein E. Andersen, Ted Briscoe   +3 more
semanticscholar   +1 more source

Correcting Grammatical Verb Errors

Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, 2014
Verb errors are some of the most common mistakes made by non-native writers of English but some of the least studied. The reason is that dealing with verb errors requires a new paradigm; essentially all research done on correcting grammatical errors assumes a closed set of triggers ‐ e.g., correcting the use of prepositions or articles ‐ but ...
Alla Rozovskaya, Dan Roth, Vivek Srikumar   +2 more
openaire   +1 more source

Weaken Grammatical Error Influence in Chinese Grammatical Error Correction

2020
Chinese grammatical error correction (CGEC), a task of correcting grammatical errors in text, is treated as a translation task, where error sentences are “translated” to correct sentences. However, some grammatical errors in the training data can confuse the CGEC models and have negative influence in the “translating” process. In this paper, we propose
Jinggui Liang, Si Li
openaire   +1 more source

Generating artificial errors for grammatical error correction

Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics, 2014
This paper explores the generation of artificial errors for correcting grammatical mistakes made by learners of English as a second language. Artificial errors are injected into a set of error-free sentences in a probabilistic manner using statistics from a corpus.
Mariano Felice, Zheng Yuan
openaire   +1 more source

Neural Grammatical Error Correction for Romanian

2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), 2020
Resources for Grammatical Error Correction (GEC) in non-English languages are scarce, while available spellcheckers in these languages are mostly limited to simple corrections and rules. In this paper we introduce a first GEC corpus for Romanian consisting of 10k pairs of sentences.
Teodor-Mihai Cotet, Stefan Ruseti, Mihai Dascalu   +2 more
openaire   +1 more source