Work

The SMarT Classifier for Arabic Fine-Grained Dialect Identification

Year: 2019

Type: conference-paper

Abstract: This paper describes the approach adopted by the SMarT research group to build a dialect identification system in the framework of the Madar shared task on Arabic fine-grained dialect identification.We experimented several approaches, but we finally decided to use a Multinomial Naïve Bayes classifier based on word and character ngrams in addition to the language model probabilities.We achieved a score of 67.73% in terms of Macro accuracy and a macro-averaged F1-score of 67.31%.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/w19-4633

Authors: Karima Meftouh, Karima Abidi, Salima Harrat, Kamel Smaili

Institutions: Badji Mokhtar-Annaba University, Laboratoire Lorrain de Recherche en Informatique et ses Applications, Université de Lorraine, École Normale Supérieure de Bouzareah Alger

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2971105282

FWCI: 0.67

Cites: 27

Cited by: 8

Related to: 10