Speech Recognition And Control System Design Of Robot Based On DSP

An integrated guiding robot system need use many kinds of artificial intelligence technologies together, whose goal is to build up a man model.It is one of them that we should make the robot understand the languages. The speech recognition system of the robot, which is the important part of theguiding robot head, mainly recognizes the voice and makes the decision, then gives out the action instruction to control the robot. The robot should recognize the voice of nonspecial persons. When receiving speech signals, it preprocesses the speech, detects the end point and extracts characteristic vector. Then it gives out the recognition results through the pattern matching of the characteristic vector in the speech bank. The recognition ranges of the robot are decided by the trained speech bank, in which the special speech matches the special action.The traditional robot hearing system usually controls the robot using PC as the running platform of the system. Its traits are as following: it uses a computer as the information processing core of the robot to control it through the interface circuit.Its processing ability is quite powerful, and speech bank is complete.At last it is quite easy to renew the system and develop the function.But it also has some disadvantages, firstly it is a little heavy, which makes the robot unavailable in the conditions of miniaturization and complexity. Then its power consumption is high and costs much.In the recent years, the improvement of the microprocessor performance promotes the robot to develop fast, especially the appearance of DSP which has mass memory and high-speed operation makes it possible that a robot can complete the complex speech signal processing and action instruction off line.In this paper TMS320VC5509 and TLV320AIC23 are made together to be the speech acquisition system of a robot in the hardware. DSP is used to be the speech recognition processor, whose processing speed is quite fast. CCS 3.1 is used to finish configuring the peripheral interface of DSP. In development of the software the characteristics of speech signals are analyzed, speech signals are preprocessed and detected by end points. Speech eigenvector adopts MFCC, and pattern matching and...