Speaker recognition anti-noise system research based on RLS and GFCC

In order to improve the performance of speaker recognition system in noisy environment, a RLS adaptive filter as preprocessor to remove noise is presented, to further improve the SNR of speech signal, and then through the Gammatone filter bank to deal with the speech signal after denoising, extracting the feature parameter GFCC, which is used for speaker recognition. Simulation experiment is conducted with Gaussian mixture model based speaker recognition system. The experimental results show that the proposed algorithm significantly improves system recognition rate and robustness in noisy environment.