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NLP in Sign Language Recognition Boon for Dumb People

Brijkishor Soni, Harsh Kumar Jarwal, Alankrita Agrawal

Abstract


In order to help and provide facility to the persons who have vocal and hearing problems to communicate, this study provides a design innovative system. It discusses an improving technique for speech-to-sign translation and sign language recognition. The created method uses skin colour segmentation to extract indications from video sequences with a dynamic and minimally crowded background. It separates out the relevant feature vectors from dynamic movements and gives room in static motions. Support vector machines are used for this classification. Voice recognition is based on the pyramid standard module. According to experimental findings, signs may be satisfactorily segmented against a variety of backdrops, and gestures and speech recognition are comparatively accurate.


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