Robustness to telephone handset distortion in speaker recognition by discriminative feature design

摘要

A method is described for designing speaker recognition features that are robust to telephone handset distortion. The approach transforms features such as mel-cepstral features, log spectrum, and prosody-based features with a non-linear artificial neural network. The neural network is discriminatively trained to maximize speaker recognition performance specifically in the setting of telephone handset mismatch between training and testing. The algorithm requires neither stereo recordings of speech during training nor manual labeling of handset types either in training or testing.