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AUTOVISION - SPEECH BASED FEEDBACK SYSTEM FOR THE OPTICALLY DAMAGED PEOPLEUSING RASPBERRY PI

Authors: Remegius Praveen Sahayaraj L. and Mohamed Irfan A.;

AUTOVISION - SPEECH BASED FEEDBACK SYSTEM FOR THE OPTICALLY DAMAGED PEOPLEUSING RASPBERRY PI

Abstract

There are millions of people around the globe with various kinds of visual defects and blindness known as Optically Damaged People. As everything is dark for Optically Damaged People, they usually perform daily tasks based on calculations. This project aims to help the blind society to experience the world independently with the help of a speech-based feedback system. This project proposes (1) text recognition and text-to-speech, (2) identify and locate specific types of objects **and walking navigation which can be incorporated into this project as a future scope.** Our project will help a visually-impaired person to walk easily by detecting obstacles in front of them and thus avoid it. It will help them read texts as well, which is done using** OCR which uses python and an API for the text recognition. Thereafter, GTTS is used to convert text to speech, which is the final output for the users.

Keywords

Object Detection Optically Damaged Text Recognition Camera Module Text-Speech Conversion gTTS Audio Jack Raspberry Pi

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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