A DGMMBASED CHINESE SIGN LANGUAGE RECOGNITION SYSTEM

Sign language is the language used by the deaf, which is a comparatively steadier expressive system composed of signs corresponding to postures and motions assisted by facial expression. It is communication using motion/vision. The objective of sign language recognition research is to “see” the language of the deaf. The integration of sign language recognition and sign language synthesis jointly comprise a “human computer sign language interpreter”, which facilitates the interaction between the deaf and their surroundings. The issue of sign language recognition is to recognize dynamic gesture signal, that is, to recognize sign language signal. Considering real time property and recognition performance of the system, Cyberglove is selected as the gesture input device in the system under discussion and DGMM（dynamic Gaussian mixture model） is used as a recognition technique, which models sign language signal by a time varying density function composed of M N Gaussian mixture density function. The system can recognize 274 sign language words coming from the dictionary of Chinese sign language with the accuracy of 98.2%. Compared with the recognition system based on HMM, the recognition rate of DGMM is nearly equal to that of HMM, and the training and recognition speed of DGMM is apparently much faster than that of HMM.