Text to Speech Conversion using Optical character Recognition for Visually Impaired Persons

2015 ◽  
Vol 29 (2) ◽  
pp. 97-102
Author(s):  
Prince saini ◽  
◽  
Rajesh Mehra
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Text To Speech ◽  
Optical Character ◽  
Visually Impaired Persons

scholarly journals Hardware and Software Co-Design of Arabic Alphabets Recognition Platform for Blind and Visually Impaired Persons

2017 ◽  
Vol 11 (1) ◽  
pp. 193-200
Author(s):  
Brahim Sabir ◽  
Yassine Khazri ◽  
Mohamed Moussetad ◽  
Bouzekri Touri
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Recognition Algorithm ◽  
Hardware Platform ◽  
Blind And Visually Impaired ◽  
Optical Character ◽  
Printed Text ◽  
Visually Impaired Persons ◽  
Text Images

Background:Optical character Recognition (OCR) is a technic that converts scanned or printed text images into editable text. Many OCR solutions have been proposed and used for Latin and Chinese alphabets.However not much can be found about OCRs for the handwriting scripts Arabic Alphabets, and especially to be used for blind and visually impaired persons.This paper has been an attempt towards the development of an OCR for Arabic Alphabets dedicated to blind and visually impaired persons.Method:The proposed Optical Arabic Alphabets Recognition algorithm includes binarization of the inputted image, segmentation, feature extraction and a classification based on neural networks to match read Arabic alphabets with trained pattern.The proposed algorithm has been developed using Matlab, and the solution was designed to be implemented on hardware platform and can be customized for mobile phones.Conclusion:The presented method has the benefit that the accuracy of recognition is comparable to other OCR algorithms.

scholarly journals Optical Character Reader & Text To Speech Conversion using Correlations & Speech Synthesis

2020 ◽  
Vol 9 (10) ◽  
pp. 478-483
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Speech Synthesis ◽  
Figurative Language ◽  
Text To Speech ◽  
Rate System ◽  
Written Text ◽  
Optical Character ◽  
Effective Manner ◽  
High Level

In the modern era of image processing, recognizing content or information from an image is process of electronic conversion into machine encoded text. Advanced systems that are capable of producing high accuracy for multi-font recognition are now becoming commonplace, and with the support of digital consent formatting. Some programs are able to retrieve formats that are very close to the original page including images, columns, and other non-text items. Proposed system is able to recognize text from an image and convert it into editable text along with speech conversion. System uses Correlation model for OCR (Optical Character Recognition) and Speech Synthesis for TTS (Text To Speech) conversion. Correlation is a measurement of the similarities between two similar objects such as the predefined alphabets and recognizing a combination of those alphabets from an image. Speech synthesis is an artificial expression of human speech. The computer program that has been used this feature is called a speech computer as well as speech synthesizer that can be implemented on the basis of software or hardware primitives. The text-to-speech system (TTS) converts a standard language text into a speech; some programs provide figurative language presentations such as typed text in speech. System is capable enough to acquire high level of accuracy with less false recognition. It is required to built an effective text scanner that can recognize text from an image with less error rate. System has been implemented in MATLAB and various pre-processing filters have been applied for better enhancement and extraction. Hand written text can also be recognized with an effective manner.

Optical character recognition reading aid for the visually impaired

2008 ◽  
Vol 30 (5) ◽  
pp. 441-443 ◽  
Author(s):  
Juan Carlos Grandin ◽  
Fabián Cremaschi ◽  
Elva Lombardo ◽  
Ed Vitu ◽  
Manuel Dujovny
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Optical Character

scholarly journals A Smart Reader for Blind People

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1566-1568
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Raspberry Pi ◽  
Human Communication ◽  
Human Needs ◽  
Normal People ◽  
Optical Character ◽  
Visually Impaired People ◽  
Visually Challenged

This paper presents an intelligent bot for aiding the visually challenged people. Presently, 81% are visually impaired who live in the developing countries. Nowadays Human communication is mainly focused on text and speech. To read the text a human needs a vision. Survey conducted on several papers and systems provides hardware consisting of a camera interface with Raspberry Pi for processing the text. The camera captures text image of a handwritten or printed text. The raspberry pi makes use of Optical Character Recognition (OCR) software installed in it, to perform the conversion of an image to text and similarly text to speech conversion. The assistant is applicable for visually impaired people as well as for normal people in order to increase their level of comfort.

scholarly journals Model for Converting PDF to Audio Format (Listen Your Book)

2021 ◽  
Vol 9 (VII) ◽  
pp. 3203-3206
Author(s):  
Shailendra Singh
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Efficient Technique ◽  
Text To Speech ◽  
Multiple Methods ◽  
Optical Character ◽  
Visually Impaired People ◽  
The People ◽  
Textual Content ◽  
Text Images

The present paper has introduced an innovative and efficient technique that enables user to hear the contents of text images instead of reading through them. In the current world, there is a great increase in the utilization of digital technology and multiple methods are available for the people to capture images. such images may contain important textual content that the user may need to edit or store digitally. It merges the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS). This can be done using Optical Character Recognition with the use of Tesseract OCR Engine. OCR is a branch of AI that is used in applications to recognize text from scanned documents or images. The analyzed text can also be converted to audio format to help visually impaired people hear the content that they wish to know. Text-to-Speech conversion is a method that scans and reads alphabets and numbers that are in the image using OCR technique and convert it into voices. The aim is to study and compare the multiple methods used for STT conversions and to figure out the most efficient technique that can be adapted for the conversion processes. As a result, based on review study it is found that HMM is a statistical model which is most suitable for TTS conversions.

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