Language Model for Translating the English Language to Garhwali Language

Abstract

The main aim of this paper is to develop a language model for translating the English language to Garhwali, a language spoken in the Garhwal region of Uttarakhand, India. The model will use state-of-the-art natural language processing techniques, including machine learning and neural networks, to enable accurate and efficient translation of English sentences into Garhwali and vice versa. The model will be trained on a large dataset of parallel English-Garhwali text to ensure high accuracy and fluency of the translations. The successful development of this language model will help bridge the language barrier between English speakers and Garhwali speakers, facilitate communication and exchange of ideas, and promote cultural exchange and understanding. Local language conversion system can help to improve the user experience by providing content in the language that the user is most comfortable with. It can help to reduce confusion and frustration, and make the user experience more enjoyable. Keywords: Statistical Machine Translation, Mathematical model, English-Garhwali, Evaluation.