ISOLATED WORD REAL TIME ETHIOPIAN SIGN LANGUAGE RECOGNITION FOR SEXUAL REPRODUCTIVE HEALTH USING KINECT

There above 1.15 Million peoples with deafness in Ethiopia with their primary means of communication called EthSL which is one of the linguistically minor languages in Ethiopia. Automatic Sign Language Recognition is currently in its infant stage while automatic speech recognition is commercially available nowadays. Currently all commercial translation services are human based, and therefore expensive, due to the need for experienced translators. There are very few sign language interpreters in Ethiopia in hospitals and interpretation prices and very costly, in addition to the cost of interpreters there is a series problem related to Sexual Health Reproduction where the patient personal information is exposed to the interpreter or family member and friend most of the time so the patient will not tell some of the required information to the doctor due to the third party interference, this research work is dedicated to overcome this problem which proposes a real-time isolated word sign language recognition for selected SRH words in hospitals and different health centers. This thesis used a depth sensing device called Kinect to capture the sign language sequences and pass it to our classification algorithms