Speech control of robotic hand augmented with 3D animation using neural network

Abstract

In this paper, speech control of robotic hand augmented with 3D animation system has been proposed and presented. Artificial neural network is employed for speech recognition method with tansig and softmax transfer function in hidden layer and output layer. Stream processing method is incorporated for processing the input signal in real time. Thirteen features in frequency domain and time domain that are commonly used in the EMG analysis are utilized in this system. To reduce the influence of noise, voice in noisy environment in the room is recorded as training data set. From the experimental results in offline speech recognition, ANN can recognize the voice command with very high accuracy. In the online real time speech recognition incorporating stream processing, the recognition accuracy decreased about 10%. The proposed speech control of robotic hand augmented with 3D animation is reliable enough with noisy environment.