The Application Of Wireless Speech Control System In ASR Robot

Speech-control is one of the most important human-machine interactive methods. Now, most of the research of speech-control is based on PC and without consideration of the noise. But the environment where robot works is various, so the speech signal maybe corrupted by various noises. Without eliminating them, the corrupted speech signal maybe useless for us. This thesis uses Msp430F149 from TI corp. as the micro processer in wireless transmitter system. Although Msp430F149 does not have the same hardware resourses for speech signal processing as DSP does, Msp430F149 has an attractive trait as the low power consumption. Because the remote control robots system works consistently for a long time and the speech orders are very simple, the lower power consumption matters the most. Otherwise, using digital-filiter in software can offset the shorten of hardware.The main work of this thesis can be separated into three parts:1. Signal Conditioning: A good analog front end is a need for digital signal processing. As for the speech signal, on one hand, it should be amplified because the output signal of microphone is feeble, on the other hand, it is a wide band signal and the sample rate of analog to digital converter( ADC) is finite, so an anti-aliasing filter is need to be added before it gets into the ADC.2. Analog to Digital Converter: The attenuation rate from pass-band to stop-band is finite in any real low pass filter. If we design a signal processing system only awkwardly following Nyquist Theorem, aliasing will be introduced into the system for the non-ideal anti-aliasing filter. In this thesis, the over-sampling Techniques are adopted to solute this problem. It can help us in two ways. First, it is an effective way to eliminate the aliasing. Second, it can improve the Signal to Noise Ratio( SNR)in an ADC, which equals to improve the precision of conversion.3. ADPCM Aalgorithm: Due to the amount of sampling data that the wireless chip nRF401 transmits, the whole transmission job takes a long time which obviously slow the system down. This thesis uses ADPCM algorithm to zip the sampling data from 16 bits to 4 bits in sending part, however, in receiving part, ADPCM unzips data from 4 bits to 16 bits.