Humanizing the Chatbot with Semantics based Natural Language Generation


This paper introduces approach made for improving the efficiency of the chatbot or artificial conversational entity used in various commercial and banking sector. Humanizing is to improving the response generation ability of the chatbot. In this work, an attempt has been made to generate more natural response for a question asked to an artificial conversational entity by using various Natural Language Processing (NLP) and Natural Language Generation (NLG) techniques. Paraphrase generation plays a main role by generating semantically similar response for a query making it more natural.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL