Fuzzy-Based Sign Language Interpreter
Sign language is a language through which communication is possible for the deaf–dumb community. It is the only communication mean for that physically challenged people. But the hearing people never try to learn the sign language. So the deaf people cannot interact with the normal people without a sign language interpreter. Sign language depends on sign patterns, i.e., orientation and movements of the arm to facilitate understanding between people. This paper presents a methodology which recognizes the sign language using fuzzy logic controller and translates into a normal text and speech. This system uses glove fitted with flex sensors, inertial measurement unit (IMU) to gather data on each finger’s position to recognize their sign symbol using fuzzy control algorithm. After defuzzifying the output, it sends a unique set of signals to the PIC microcontroller with speak jet IC which is preprogrammed to speak desired sentences and also speech recognizing module is interfaced with microcontroller for converting voice to text.
KeywordsInertial measurement unit Digital image process technique Hidden Markov model Artificial neural networks Fuzzy logic Kinect platform
I wish to thank Mr. S. Vijayakumar, Assistant Professor, for being my guide, whose keen interest and advice at various stages of this project made me to work harder and execute this assignment.
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