Search Results for author: Bashar Talafha

Found 7 papers, 2 papers with code

Bench-Marking And Improving Arabic Automatic Image Captioning Through The Use Of Multi-Task Learning Paradigm

no code implementations11 Feb 2022 Muhy Eddin Za'ter, Bashar Talafha

The results showed that the use of multi-task learning and pre-trained word embeddings noticeably enhanced the quality of image captioning, however the presented results shows that Arabic captioning still lags behind when compared to the English language.

Image Captioning Multi-Task Learning +1

Multi-Dialect Arabic BERT for Country-Level Dialect Identification

1 code implementation COLING (WANLP) 2020 Bashar Talafha, Mohammad Ali, Muhy Eddin Za'ter, Haitham Seelawi, Ibraheem Tuffaha, Mostafa Samir, Wael Farhan, Hussein T. Al-Natsheh

Our winning solution itself came in the form of an ensemble of different training iterations of our pre-trained BERT model, which achieved a micro-averaged F1-score of 26. 78% on the subtask at hand.

Dialect Identification Language Modelling

Mawdoo3 AI at MADAR Shared Task: Arabic Tweet Dialect Identification

no code implementations WS 2019 Bashar Talafha, Wael Farhan, Ahmed Altakrouri, Hussein Al-Natsheh

Arabic dialect identification is an inherently complex problem, as Arabic dialect taxonomy is convoluted and aims to dissect a continuous space rather than a discrete one.

Dialect Identification

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