StoryGenAI: An Automatic Genre-Keyword Based Story Generation

Story Generation through Deep Learning is a fascinating area of research in Artificial Intelligence that aims to create computer systems that can produce original and compelling narratives and is an interesting concept that has flourished in the domain of Machine Learning applications starting from 2018. Most of the research carried out in this specific area has shown advances in Modelling and efficiency of story generation. However, some of the setbacks in Artificial Story Generation include little to no coherency with human generating pattern, tokens/words limitation, missing plot twists and direction of story. In this paper, we have performed a comparative study on Automatic Story Generation as well as the proposed scheme of this paper has main focus on generating a meaningful story with the help of conditional text generation using keywords upto five hundred words by optimizing hugging face generative pre trained model Version Two catering towards the problem of coherency in the text generated. As a result each sentence is semantically coherent and the first three sentences are indeed related to the title itself. The experimental results show a BLEU score of 0.704 averaging over ten genres.