Speech based Research on Marathi Educational Chatbot

In any interactive agent, providing a suitable answer plays a vital role in determining the success of that chatbot. Speech recognition API and google translate API are used to recognize the user's voice and text translation respectively. In this paper, Marathi speech based educational chatbot is proposed using naive bayes classifier. After performing preprocessing, Naive Bayes classifier is used to determine and evaluate the highest probable class. Nearly 1600 words are used to train the model. The proposed approach is tested with some questions and their topics in the dataset. Brute force keyword matching and string similarity algorithms are implemented to fetch the suitable answer. Confusion matrix is generated to evaluate the performance of classification model.