@article{10.1145/3432246,
author = {Mishra, Santosh Kumar and Dhir, Rijul and Saha, Sriparna and Bhattacharyya, Pushpak},
title = {A Hindi Image Caption Generation Framework Using Deep Learning},
year = {2021},
issue_date = {April 2021},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {20},
number = {2},
issn = {2375-4699},
url = {https://doi.org/10.1145/3432246},
doi = {10.1145/3432246},
abstract = {Image captioning is the process of generating a textual description of an image that
aims to describe the salient parts of the given image. It is an important problem,
as it involves computer vision and natural language processing, where computer vision
is used for understanding images, and natural language processing is used for language
modeling. A lot of works have been done for image captioning for the English language.
In this article, we have developed a model for image captioning in the Hindi language.
Hindi is the official language of India, and it is the fourth most spoken language
in the world, spoken in India and South Asia. To the best of our knowledge, this is
the first attempt to generate image captions in the Hindi language. A dataset is manually
created by translating well known MSCOCO dataset from English to Hindi. Finally, different
types of attention-based architectures are developed for image captioning in the Hindi
language. These attention mechanisms are new for the Hindi language, as those have
never been used for the Hindi language. The obtained results of the proposed model
are compared with several baselines in terms of BLEU scores, and the results show
that our model performs better than others. Manual evaluation of the obtained captions
in terms of adequacy and fluency also reveals the effectiveness of our proposed approach.Availability
of resources: The codes of the article are available at https://github.com/santosh1821cs03/Image_Captioning_Hindi_Language;
The dataset will be made available: .},
journal = {ACM Trans. Asian Low-Resour. Lang. Inf. Process.},
month = mar,
articleno = {32},
numpages = {19},
keywords = {hindi, attention, deep-learning, Image captioning}
}