Recogniition and Speech Conversion of Devnagri Script using CNN

Abstract

In this paper, we are introducing an innovative, efficient, and real-time handwritten text-to-speech conversion technique for the Devanagari script. It combines the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS). This type of system can be helpful for visually impaired persons, for reading the number plates of a vehicle, and for medical applications. Text extraction from colored images is a challenging task in computer vision, for that, we have trained our model using Convolution Neural Network (CNN) with 1000s of different handwriting styles written by different people and of different age groups for each character. A trained model has been used for the recognition of input characters which was taken from the gesture movement of a fingertip with blue ink. The system is developed in Python 3.6.0.