Research Article
NLP Based Automated Language Translation Leveraging
@INPROCEEDINGS{10.4108/eai.28-4-2025.2357957, author={CH Amarendra and Ch Sai Santosh and A Nehasri and P Eisha Madhavi and Y Venkata Sivanarayana}, title={NLP Based Automated Language Translation Leveraging}, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part I}, publisher={EAI}, proceedings_a={ICITSM PART I}, year={2025}, month={10}, keywords={nlp machine translation bert gpt english to telugu english to hindi transformer models parallel corpora bleu rouge meteor translation fluency multilingual communication}, doi={10.4108/eai.28-4-2025.2357957} }- CH Amarendra
Ch Sai Santosh
A Nehasri
P Eisha Madhavi
Y Venkata Sivanarayana
Year: 2025
NLP Based Automated Language Translation Leveraging
ICITSM PART I
EAI
DOI: 10.4108/eai.28-4-2025.2357957
Abstract
Active involvement in multilingual communication is crucial in today’s globalized world. This NLP task machine translation system provides translation between English, Telugu and Hindi using hybrid attention, multi-stage fine-tuning and reinforcement learning with human feedback. These innovative methods improve accuracy, coherency, and flexibility of translations with higher fluency and context retention. The system incorporates explainable AI to evaluate the quality of translation and continuously update the model parameters in response to user feedback. By introducing cross-lingual data augmentation, our method effectively improves translation speed, especially for low-resource languages. Evaluation on benchmark measures including BLEU, ROUGE and METEOR showed significant gain in translation accuracy, validating its effectiveness for practical use from education, economy to medical scenarios. The integration of explainability makes our model transparent and trustworthy, thus applicable to different industries.
