Generating Image Captions in Arabic using Root-Word Based Recurrent Neural Networks and Deep Neural Networks
Year: 2018
Type: conference-paper
Abstract: Image caption generation has gathered widespread interest in the artificial intelligence community.Automatic generation of an image description requires both computer vision and natural language processing techniques.While, there has been advanced research in English caption generation, research on generating Arabic descriptions of an image is extremely limited.Semitic languages like Arabic are heavily influenced by root-words.We leverage this critical dependency of Arabic to generate captions of an image directly in Arabic using root-word based Recurrent Neural Network and Deep Neural Networks.Experimental results on datasets from various Middle Eastern newspaper websites allow us to report the first BLEU score for direct Arabic caption generation.We also compare the results of our approach with BLEU score captions generated in English and translated into Arabic.Experimental results confirm that generating image captions using root-words directly in Arabic significantly outperforms the English-Arabic translated captions using state-of-the-art methods.
DOI: 10.18653/v1/n18-4020
Author: Vasu Jindal
Institution: The University of Texas at Dallas
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2805430858