Wireless Gesture and Voice Recognition
Human-robot voice interface has a key role in many application fields. Robotics has achieved its greatest success to date in the world industrial manufacturing. Hand gesture is a very natural form of human interaction and can be used effectively in human computer interaction (HCI). The approaches for analyzing and classifying hand gestures for HCI include glove-based techniques and vision based techniques. The paper discussed glove-based techniques that use sensors to measure the positions of the fingers and the position of the hand in real-time. To implement the approach on real time application, the personal computer interface will be designed to control the movement of four degree of freedom (DOF) didactic robot arm by transmitting the commands using wireless circuits. For better rate of recognition, a preprocessing step for speech signal based on Kalman Filter will be used. Paper focuses on wireless Data Gloves which will be used for gesture recognition and accordingly robot movement will take place. The proposed work is the recognition of isolated words from a limited vocabulary in the presence of background noise. To reduce the effect of stationary noise (mainly environment noise) pre-processing stage is added based on Kalman Filter. The application is speaker-dependent. Therefore, it needs a training phase. It should, however, be pointed out that this limit does not depend on the overall approach but only on the method with which the reference patterns were chosen.