The application of information fusion in the real-time monitoring system

This paper studies the feasibility of information analysis processing technology, which fuses speech and image together in the real-time monitoring system. It emphasizes particularly on speech analysis and fuses these two technologies in terms of scoring strategy. It also makes some improvement on MFCC feature extraction and proposes a quick MFCC algorithm. The proposed algorithm can reach the requirement of real-time system in case of the high precision. To prove it, this paper compares its algorithm with LPC and FFT. The experiment indicates that the EER of LPC is 13.9% and the EER of FFT is 11.1%, but by using the Quick MFCC the EER is only 4.2%. And compared with the traditional MFCC algorithm, the quick MFCC algorithm reduces the run time greatly while maintaining recognition accuracy of the system. Finally the rate of fusion recognition is about 97.8%, which is a good result for the real-time monitoring system.