Robust speaker recognition integrating pitch and Wiener filter

Abstract

Speaker recognition (SR) obtains excellent results in clean speech. But noise or channel mismatch causes significant performance degradation in practical appliances. The paper focuses on resolving those problems in robust and efficient speaker identification (SI) in noisy environments. And it mainly contributes in two areas: signal processing based on Wiener filtering and speaker features integration of pitch and mel-frequency cepstrum coefficients (MFCC). It is shown in the experimental results on the YOHO corpus that the Wiener filter is an efficient front-end processing technique and pitch is a robust feature for SR in noisy environments.