Enhanced Auto Language Prediction with Dictionary Capsule -- A Novel
  Approach
Pinni Venkata Abhiram Ananya Rathore Abhir Mirikar Hari Krishna S Sheena Christabel Pravin Vishwanath Kamath Pethri Manjunath Lokanath Belgod Reetika Gupta K Muthukumaran
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.