【摘要】 手语是聋人使用的语言 ,是由手形动作辅之以表情姿势由符号构成的比较稳定的表达系统 ,是一种靠动作 /视觉交际的语言 .手语识别的研究目标是让机器“看懂”聋人的语言 .手语识别和手语合成相结合 ,构成一个“人 -机手语翻译系统”,便于聋人与周围环境的交流 .手语识别问题是动态手势信号即手语信号的识别问题 .考虑到系统的实时性及识别效率 ,该系统选取 Cyberglove型号数据手套作为手语输入设备 ,采用 DGMM( dynamicGaussian mixture model)作为系统的识别技术 ,并根据中国手语的具体特点 ,在识别模块中选取了多层识别器 ,可识别中国手语字典中的 2 74个词条 ,识别率为 97.4 % .与基于单个 DGMM的识别系统比较 ,这种模型的识别精度与单个 DGMM模型的识别精度基本相同 ,但其识别速度比单个 DGMM更多还原

【Abstract】 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. And it is a language communicated by 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 comprises a “human computer sign language interpreter”, which facilitates the interaction between deaf people and their surroundings. The issue of sign language recognition is to recognize dynamic gesture signal, that is, to recognize sign language signal. Considering the speed and performance of the recognition system, Cyberglove is selected as gesture input device in sign language recognition system, DGMM (dynamic Gaussian mixture model) is used as recognition technique, and hierarchical recognizer is used in recognizing module, which can recognize 274 sign language words coming from the dictionary of Chinese sign language with an accuracy of 97.4%, based on Chinese sign language’s own characteristic. Compared with the recognition system based on single DGMM recognizer, the recognition rate of hierarchical DGMM recognizer is nearly equal to that of single DGMM recognizer, but its recognition speed is apparently much faster than that of single DGMM recognizer.更多还原