Abstract:
Chatbots are user-friendly interfaces that emulate human dialogue. With the rise of technologies such as Artificial Intelligence (AI) and Natural Language Processing (NLP), chatbots have become an effective tool in most conversational applications of companies. India is a multiverse country that demands making the chatbot functional in different languages. We present an effective approach to building a multilingual chatbot in Indian languages for fixed-response questions. This technique omits the expensive machine translation task with a large run-time overhead. We implement the chatbot's functionality to answer the query in context by fine-tuning the transformer model to the downstream task of question-answering. The MuRIL BERT model provides the best results for correct response prediction among major multilingual BERT models