Work

NLPeople at NADI 2023 Shared Task: Arabic Dialect Identification with Augmented Context and Multi-Stage Tuning

Year: 2023

Type: conference-paper

Abstract: This paper presents the approach of the NLPeople team to the Nuanced Arabic Dialect Identification (NADI) 2023 shared task.Subtask 1 involves identifying the dialect of a source text at the country level.Our approach to Subtask 1 makes use of language-specific language models, a clustering and retrieval method to provide additional context to a target sentence, a fine-tuning strategy which makes use of the provided data from the 2020 and 2021 shared tasks, and finally, ensembling over the predictions of multiple models.Our submission achieves a macro-averaged F1 score of 87.27, ranking 1st among the other participants in the task.

Source: Arabic Natural Language Processing Conference (ArabicNLP)

DOI: 10.18653/v1/2023.arabicnlp-1.68

Authors: Mohab Elkaref, Movina Moses, Shinnosuke Tanaka, James Barry, Geeth Mel

Institution: IBM (United States)

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4389518265

FWCI: 0.354

Cites: 6

Cited by: 2

Related to: 10