A Survey of Punjabi Language Translation using OCR and ML

The use of Natural Language Processing (NLP) in machine translation has grown in significance as technologies as well as computers have become more prevalent in our daily lives. This essay's goal is to evaluate the work done in the field of natural language processing (NLP) to translate the Gurmukhi script, which is primarily used to represent the Punjabi language. Together with Hindi and Punjabi, the languages written throughout the Gurumukhi script has more than 1.5 billion native users, making it among the most used language worldwide. However, there is limited research available on the Gurmukhi script. The study presented in this paper focuses on using machine learning and AI techniques to translate written Gurmukhi text into Hindi and English languages. The input for the translation process will be in the form of machine-printed Gurmukhi text, while the output will be provided in both Hindi and English languages. The goal of this study is to enhance how well global languages absorb information and technology, making it easier and more accurate to translate from regional languages. In conclusion, the paper provides a comprehensive review of the work related to the translation of Gurmukhi script using NLP techniques, with a focus on the use of machine learning and AI. The findings of this study can contribute to the development of more advanced and accurate translation systems, making the exchange of information and knowledge more accessible for people who speak different languages.