INDIAN SIGN LANGUAGE RECOGNITION BY USING DEEP LEARNING

Abstract

Sign Language (SL) is a language through which normal people use to interact with disabled people. Nowadays days Sign language is getting more and more attention in the field of research due to its wide use in many fields. Signs and gestures are a form of communication that uses descriptive words and expressions as well as facial expressions and body movements replacing spoken words. In this world, there are many different languages, just as there are many languages. Gestures and facial expressions are often used by people who do not have the ability to hear or speak, and they use them to express their thoughts and speech. In old times gestures and hand movements were the only way to interact with each other because there was no speech or language and sign is the only way to considered for communication. However as time passed the use of the SL has become more common to people who are deaf and impaired. Commonalities can easily interact and communicate easily but people who are deaf and speech impaired have difficulty communicating with other listening people. Sign language is a communication hurdle for deaf people. People with hearing and speech impairments use various forms of communication that do not involve gestures. Therefore, the use of speech recognition technology can be beneficial for deaf people. This article presents a method for automatic recognition of Hindi fingerprints. Here, gesture-shaped signals are given as access to the system. Several additional steps are performed on the image input symbol. The segmentation stage is first done according to skin colour to see the image of the logo. The detected area is then converted into a double-barreled image. The modified Euclidean distance is then applied to the binary image. Line and line projections are used for distance-converted images. The average time and HU time are used for distance special withdrawals. Use neural networks and SVM for classification Therefore the use of speech recognition technology can be beneficial for deaf people.