Research on Noise Compensation for Text-Independent Speaker Identification

When background noise exists in the testing environment, the performance of most current speaker Identification Systems is seriously affected because the noise leads a mismatch between the training environment and the testing environment. In order to improve the identification rate, this paper studies a kind of method that makes the compensated VQ codebooks approach the codebooks trained in the testing environment by compensating the codebooks in the linear spectral domain. The experiments in the conditions with different SNRs have been done to compare compensation method with common one. The result shows the noise compensation method can improve the identification rate a lot .