Smart Summarizer for Blind People

TL;DR

This paper presents a system that summarizes news articles and converts them to speech to assist visually impaired individuals, utilizing various algorithms and APIs for text processing and speech synthesis.

Contribution

It introduces an efficient news summarization and speech conversion system specifically designed to aid blind people, integrating multiple algorithms and APIs.

Findings

Effective summarization of news articles into keywords

Conversion of summarized text to speech for accessibility

Implementation of multiple algorithms for text analysis

Abstract

In today's world, time is a very important resource. In our busy lives, most of us hardly have time to read the complete news so what we have to do is just go through the headlines and satisfy ourselves with that. As a result, we might miss a part of the news or misinterpret the complete thing. The situation is even worse for the people who are visually impaired or have lost their ability to see. The inability of these people to read text has a huge impact on their lives. There are a number of methods for blind people to read the text. Braille script, in particular, is one of the examples, but it is a highly inefficient method as it is really time taking and requires a lot of practice. So, we present a method for visually impaired people based on the sense of sound which is obviously better and more accurate than the sense of touch. This paper deals with an efficient method to summarize news into important keywords so as to save the efforts to go through the complete text every single time. This paper deals with many API's and modules like the tesseract, GTTS, and many algorithms that have been discussed and implemented in detail such as Luhn's Algorithm, Latent Semantic Analysis Algorithm, Text Ranking Algorithm. And the other functionality that this paper deals with is converting the summarized text to speech so that the system can aid even the blind people.