文章基本信息

标题：Dialect Identification in NuancedArabic Tweets Using Farasa Segmentation andAraBERT
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作者：Anshul Wadhawan
期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2021
卷号：2021
页码：291-295
语种：English
出版社：ACL Anthology
摘要：This paper presents our approach to address the EACL WANLP-2021 Shared Task 1: Nuanced Arabic Dialect Identification (NADI). The task is aimed at developing a system that identifies the geographical location(country/province) from where an Arabic tweet in the form of modern standard Arabic or dialect comes from. We solve the task in two parts. The first part involves pre-processing the provided dataset by cleaning, adding and segmenting various parts of the text. This is followed by carrying out experiments with different versions of two Transformer based models, AraBERT and AraELECTRA. Our final approach achieved macro F1-scores of 0.216, 0.235, 0.054, and 0.043 in the four subtasks, and we were ranked second in MSA identification subtasks and fourth in DA identification subtasks.