Emblem: Sign Language Recognition Based on Convolutional Neural Network

Emblem: Sign Language Recognition Based on Convolutional Neural Network

Roshani A.Ahire , Poonam R. Gaikwad, Aishwarya A. Bhamre, Amol K. Kharule, Harshal V. Kadam

Department of computer Engineering

Brahma valley college of Engineering, Nashik. Maharashtra, India

Abstract- Voice and Language is the main thing for human to communicate with each other. Due to hearing ability we can understand thoughts of each other. Even nowadays we can give commands using voice recognition. But what if one absolutely cannot hear anything and eventually cannot speak. So The Sign Language is the main communicating tool for hearing impaired and mute people, and also to ensure an independent life for them, the automatic interpretation of sign language is an extensive research area. With the use of image processing and artificial intelligence, many techniques and algorithms have been developed in this area. Every sign language recognition system is trained for recognizing the signs and converting them into required pattern. The proposed system aim to provide speech to speechless, in this paper the double handed Indian Sign Language is captured as a series of images and it’s processed with the help of Python and then it’s converted to speech and text.

Index Terms- Convolutional neural network, Gesture recognition, Image processing, conversion, American sign language, image processing, convolutional neural network, data glass.