Bookease Smart Novel Summarizer

Abstract

The increasing availability of digital literary resources has created a need for intelligent tools that can assist 
readers in understanding and analyzing lengthy textual content efficiently. This study presents BookEase Smart 
Novel Summarizer, a web-based application designed to facilitate automated novel analysis through Natural 
Language Processing (NLP) techniques. The system is implemented using the Flask framework in Python with 
MySQL as the backend database.The proposed application accepts novels in PDF and TXT formats and performs 
extractive text summarization using frequency-based sentence ranking methods. In addition to summary 
generation, the system identifies major characters and evaluates the emotional tone of the narrative through 
VADER sentiment analysis. To provide deeper insight into story progression, an emotional arc visualization is 
generated by dividing the text into multiple segments and tracking sentiment variations throughout the novel. 
The platform further enhances reader engagement by automatically generating multiple-choice comprehension 
questions from the summarized content. Accessibility features include text-to-speech narration with synchronized 
sentence highlighting and multilingual translation support for Telugu, Hindi, Tamil, French, Spanish, and 
German. Furthermore, the application integrates a search facility that enables users to discover literary works 
from a large collection of public-domain novels available through Project Gutenberg.Experimental evaluation 
demonstrates that the proposed system effectively combines text summarization, sentiment assessment, quiz 
generation, and language accessibility within a unified framework. The developed solution serves as an intelligent 
reading assistant that can support students, researchers, educators, and general readers in exploring and 
understanding literary texts more efficiently.