Research on Voice Print Recognition Based on Wavelet Analysis and BP-GA

Yan-feng KONG, Lian-xing JIA, Jiang ZHANG


Aiming at the problems of common algorithm in voice print recognition, to improve the performance of recognition system, this paper put forward a new recognition algorithm based on wavelet analysis and BP-GA optimization algorithm. The algorithm, firstly extracts time-domain and frequency-domain characteristic variation of voice signal using wavelet transform, and then trains the variation data with BP-GA algorithm, which overcomes the problem of traditional multi-layers neural network’s local minimum value, lastly puts the trained data into a designed network to form the final voice print algorithm. Simulation experiment showed compared with current recognition algorithm, the algorithm in this paper has the advantage of fast recognition velocity, high recognition rate, low fault rate, automatic error correcting, and strong robustness with different voice-makers.


Voice print recognition, Wavelet analysis, Artificial intelligence, BP-GA


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