Faheem at NADI shared task: Identifying the dialect of Arabic tweet
This paper describes Faheem (adj. of understand), our submission to NADI (Nuanced Arabic Dialect Identification) shared task. With so many Arabic dialects being under-studied due to the scarcity of the resources, the objective is to identify the Arabic dialect used in the tweet, country wise. We propose a machine learning approach where we utilize word-level n-gram (n = 1 to 3) and tf-idf features and feed them to six different classifiers. We train the system using a data set of 21,000 tweets—provided by the organizers—covering twenty-one Arab countries. Our top performing classifiers are: Logistic Regression, Support Vector Machines, and Multinomial Na ̈ıve Bayes.
Code (0)
등록된 구현이 없습니다.
Tasks
Dialect IdentificationregressionSimilar Papers 제목 키워드 기반
Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach
In this paper, we present our approach for the "Nuanced Arabic Dialect Identification (NADI) Shared Task 2023". We highlight our methodology for subtask 1 which deals with country-level dialect identification. Recognizin…
Dialect IdentificationMulti-class Classificationspeech-recognitionSpeech RecognitionNADI 2020: The First Nuanced Arabic Dialect Identification Shared Task
We present the results and findings of the First Nuanced Arabic Dialect Identification Shared Task (NADI). This Shared Task includes two subtasks: country-level dialect identification (Subtask 1) and province-level sub-d…
Dialect IdentificationNADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task
We describe findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI 2022). NADI aims at advancing state of the art Arabic NLP, including on Arabic dialects. It does so by affording diverse datasets …
Dialect IdentificationSentiment AnalysisvalidNADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task
We describe the findings of the fifth Nuanced Arabic Dialect Identification Shared Task (NADI 2024). NADI's objective is to help advance SoTA Arabic NLP by providing guidance, datasets, modeling opportunities, and standa…
Dialect IdentificationMachine TranslationTranslationvalidArabic Dialect Identification Using BERT-Based Domain Adaptation
Arabic is one of the most important and growing languages in the world. With the rise of social media platforms such as Twitter, Arabic spoken dialects have become more in use. In this paper, we describe our approach on …
Dialect IdentificationDomain Adaptation