Results 261 to 270 of about 61,567 (299)

Constructing Artificial Features with Grammatical Evolution for the Motor Symptoms of Parkinson's Disease. [PDF]

open access: yesBioengineering (Basel)
Psathas A   +4 more
europepmc   +1 more source

SIGNAL: Dataset for Semantic and Inferred Grammar Neurological Analysis of Language. [PDF]

open access: yesSci Data
Komissarenko A   +5 more
europepmc   +1 more source

GRAMMATICAL ERRORS ON THE THESIS

open access: yes, 2019
. Grammatical errors on thesis almost happen in the entire thesis chapters. This case need to be analyzed in descriptive qualitative design. The purpose of the research was to find out grammatical errors types and factors influence it. The samples were selected randomly; 18 theses and students.
Niati, Batdal; English Education, Faculty of Teacher Training and Education, University of Pasir Pengaraian   +1 more
openaire   +4 more sources

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 0001
openaire   +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   +2 more
openaire   +1 more source

Classification and Generation of Grammatical Errors

Proceedings of the 2014 International C* Conference on Computer Science & Software Engineering - C3S2E '14, 2008
The misuse of grammar is a common and natural nuisance, and a strategy for automatically detecting mistakes in grammatical syntax is warranted. This research defines and implements a unique approach that combines machine-learning and statistical natural language processing techniques.
Anthony Penniston, Eric Harley
openaire   +1 more source

Home - About - Disclaimer - Privacy