Enhanced Auto Language Prediction with Dictionary Capsule -- A Novel Approach
Abstract
The paper presents a novel Auto Language Prediction Dictionary Capsule (ALPDC) framework for language prediction and machine translation. The model uses a combination of neural networks and symbolic representations to predict the language of a given input text and then translate it to a target language using pre-built dictionaries. This research work also aims to translate the text of various languages to its literal meaning in English. The proposed model achieves state-of-the-art results on several benchmark datasets and significantly improves translation accuracy compared to existing methods. The results show the potential of the proposed method for practical use in multilingual communication and natural language processing tasks.
Cite
@article{arxiv.2403.05982,
title = {Enhanced Auto Language Prediction with Dictionary Capsule -- A Novel Approach},
author = {Pinni Venkata Abhiram and Ananya Rathore and Abhir Mirikar and Hari Krishna S and Sheena Christabel Pravin and Vishwanath Kamath Pethri and Manjunath Lokanath Belgod and Reetika Gupta and K Muthukumaran},
journal= {arXiv preprint arXiv:2403.05982},
year = {2024}
}
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