Data Science and Intelligent Computing Techniques
Implementing Natural Language Generation through industry-specific chatbots
Authors: Ankit Kapoor and Sujala Shetty
Publishing Date: 12-01-2023
ISBN: 978-81-955020-2-8
Abstract
Natural Language Generation (NLG) is at the forefront of research in the field of Natural Language Processing (NLP) where an algorithm is taught to create text in any given language. The purpose of this research paper is to implement NLG algorithms into the design of a conventional chatbot to improve its design and make it more usable. The paper explores the details and flaws of widely used chatbot templates and aims at providing a way to resolve these issues by implementing a text generation algorithm. The task is performed by assessing an industry-specific chatbot- in this case, a medical query bot- which runs on the proposed principle. The paper also showcases an array of conversational AI’s crafted using a publicly available version of GPT 2, to further explore the scope of Natural Language Generation.
Keywords
Natural Language Processing (NLP), Natural Language Generation (NLG), Language Models, Recurrent Neural Networks (RNN), LSTM, Transformer Models, GPT 2, Language Generation, Text Prediction, Text Classification, Artificial Intelligence, Machine Learning, Deep Learning.
Cite as
Ankit Kapoor and Sujala Shetty, "Implementing Natural Language Generation through industry-specific chatbots", In: Satyasai Jagannath Nanda and Rajendra Prasad Yadav (eds), Data Science and Intelligent Computing Techniques, SCRS, India, 2023, pp. 55-67. https://doi.org/10.56155/978-81-955020-2-8-6