Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)

International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)

📍Jaipur, India🗓️ 23-24 March 2026
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Sanskrit-to-Hindi Translation of Bhagavad Gita Verses Using a Deep Learning–Based Sequence-to-Sequence Model

Authors
Kamini Solanki1, *, Nilay Vaidya1, K. Kanubhai Patel1, Nana Yaw Duodu2
1Charotar University of Science and Technology, Changa, India
2Accra Technical University, Accra, Ghana
*Corresponding author.
Corresponding Author
Kamini Solanki
Available Online 25 June 2026.
DOI
10.2991/978-94-6239-713-2_42How to use a DOI?
Keywords
Sanskrit; Hindi; Deep Neural Network; LSTM; Sequence-to-Sequence Model
Abstract

This study presents a deep learning-based Sanskrit to Hindi translation system for Bhagwad Gita verses using a sequence-to-sequence (Seq2Seq) model with an LSTM based encoder-decoder architecture. The model is trained on a parallel corpus containing aligned Sanskrit to Hindi verse pairs. Data preprocessing techniques, including tokenization and padding, are applied to the prepared input for training. The system is evaluated using standard metrics such as accuracy and BLEU score. Experimental results demonstrate that the model achieved an accuracy of approximately 92% and a BLEU score of 0.41, indicating its capability to capture linguistic patterns and generate contextually relevant translations for unseen verses, achieving an accuracy of approximately 92% and a BLEU score of 0.41. The proposed approach highlights the capability of deep learning methods in handling complex classical languages and contributes to the digital accessibility and wider dissemination of ancient Indian scripture through automated translation.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
25 June 2026
ISBN
978-94-6239-713-2
ISSN
2589-4919
DOI
10.2991/978-94-6239-713-2_42How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Kamini Solanki
AU  - Nilay Vaidya
AU  - K. Kanubhai Patel
AU  - Nana Yaw Duodu
PY  - 2026
DA  - 2026/06/25
TI  - Sanskrit-to-Hindi Translation of Bhagavad Gita Verses Using a Deep Learning–Based Sequence-to-Sequence Model
BT  - Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)
PB  - Atlantis Press
SP  - 567
EP  - 577
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-713-2_42
DO  - 10.2991/978-94-6239-713-2_42
ID  - Solanki2026
ER  -