An analysis tool involving significant Sanskrit text sentiment analysis has been developed by researchers at the Indian Institute of Technology, Roorkee. The proposed method has a machine translation accuracy of 87.50% and an accuracy of 92.83% for figuring out how someone feels about something.
Because there was not enough labelled data, these technologies could not be used to their full potential. The study suggested a method that uses sentiment analysis, machine translation, and models for judging the quality of translations.
The cross-lingual mapping of the source and target languages has been done using machine translation. The sentences that were translated into English are as natural and mature as the original English.
The Valmiki Ramayana website, which was created and is still being updated by IIT Kanpur academics, served as the source of the dataset for this study. By using only root words and the prefixes and suffixes that go with them, the researchers hope to improve classification by looking into the morphology of Sanskrit.
They also intend to assess how well the Sanskrit’s rich morphology is preserved in the English translation. Additionally, they hope to acquire a model that can recognise the context of words in many languages and offer word embeddings with smaller dimensions. A research paper describing the model has been published in the journal “Applied Intelligence.”