Native Language Identification on L2 Portuguese

Gayo, Iria

doi:10.1007/978-3-030-41505-1_9

Search citation statements

Order By: Relevance

Paper Sections

Select...

Related Work1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2020

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, other languages were considered such as the Finnish and the Norwegian languages in [6], [7], the potuguese [8] and the indien [9]. These works aimed to identify if the NLI methods earlier used in level two English can be effective to other languages.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning Model for Identifying the Arabic Language Learners based on Gated Recurrent Unit Network

Mechti¹,

Alroobaea²,

Krichen³

et al. 2020

IJACSA

View full text Add to dashboard Cite

This paper focuses on identifying the Arabic Language learners. The main contribution of the proposed method is to use a deep learning model based on the Gated Recurrent Unit Network (GRUN). The proposed model explores a multitude of stylistic features such as the syntax, the lexical and the ngrams ones. To the best of our awareness, the obtained results outperform those obtained by the best existing systems. Our accuracy is the best comparing with the pioneers (45% vs 41%), considering the limited data and the unavailability of accurate tools dedicated to the Arabic language.

show abstract