AN ENHANCEMENT OF TEXT TO SPEECH (TTS) SYSTEM USING RASPBERRY PI

Abstract

The blind man suffered greatly until the famous French inventor Louis Braille developed Braille, a form of writing invented to enable the blind to read. It did this by making characters prominent symbols on paper, allowing reading to become simple. There are already many systems that read images and give voice output. More recently, since the computer appeared in the twentieth century, things became easier for our daily life. This coincided with the beginning of the disappearance of the book as a hard copy, and electronic copy books became an urgent need in the development of reading, writing to help the visually impaired. The main problem encountered with this project was: the difficulty in the recognition of handwriting, and changes in the forms of handwriting, size and the number of paragraphs, as well as the recognition hard to extract letters containing noise from the document. The goal of this work-design system was to design a system able to extract and recognize handwriting for the visually impaired, with improved portability, to recognize the font size of lines from 8 to 10 PT handwriting using the hardware of a Raspberry Pi3 device. Another goal was to increase the valid ability of the blind people to read handwritten text. The method of work first the hardware platform used: Raspberry Pi 3 model B with inbuilt 5 MP camera, headphone; a 3D printed reader arm; second the software used: python language for after image capture of handwriting, grey scale image processing, followed by a Tesseract algorithm for sampling characters, followed by OCR and TTS, adding pronunciation capability to recognized characters. The result of this project is the ability to recognize handwriting types successfully without errors, on the condition that they are regular, as well as the ability to read capital letter and small letter handwriting without errors, and to read size 8pt text successfully.