Research On The Key Technologies Fo Speech Recognition For Robot Communication

So far the development of robot, as to the robot control, voice control is nothing but the most natural and most convenient. From the present research on voice recognition technology at home and abroad, the exchanging with robot and applying speech recognition technology to robot is becoming a hot spot of the present study.Speech recognition technology allows the robot can understand natural language. The identified information received as a voice signal is applied to a variety of robot technology. Applying the voice recognition technology to robot will bring users the greatest convenience. Therefore research and development of practical speech recognition system for robots makes great sense to the wider use of robots. The main contents of this paper are as follows:First of all, based on the basic principles of speech recognition, we research on the key technologies of robot dialogue oriented speech recognition, pre-processing of speech signal, including sampling, removing noise, endpoint detection, pre-emphasis, windowing separate frame and so on. The performance of the line Prediction Cepstral Coefficients (LPCC) and Mel Frequency Cepstral Coefficients (MFCC) are also compared and analyzed. We then study the mainstream model training and pattern-matching technology, which is the core of the speech recognition technology, including Hidden Markov Model (HMM), dynamic time warping (DTW), vector quantization (VQ), artificial neural network (ANN), HMM and ANN hybrid model, etc.Secondly, we design and complete the robot speech recognition control system, the speech recognition control software is compiled based on VC++integrated development environment. It can achieve better recognition performance and higher efficiency in the implementation of the robot voice command recognition algorithm. Finally it is tested on AS-R robot. Combined with sonar and the use of PSD sensors, it has greatly increased the interactivity of the robot.The experimental results show that the implementation of the speech recognition control system has better recognition performance. At the same time, the system is simple, cost-effective, easy-function expansion and transplantation. And it has a good prospect of broad application.