Voice source cepstrum coefficients for speaker identification

We propose a novel feature set for speaker recognition that is based on the voice source signal. The feature extraction process uses closed-phase LPC analysis to estimate the vocal tract transfer function. The LPC spectrum envelope is converted to cepstrum coefficients which are used to derive the voice source features. Unlike approaches based on inverse-filtering, our procedure is robust to LPC analysis errors and low-frequency phase distortion. We have performed text-independent closed-set speaker identification experiments on the TIMIT and the YOHO databases using a standard Gaussian mixture model technique. Compared to using melfrequency cepstrum coefficients, the misclassification rate for the

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Jon Gudnason, Mike Brookes
• Keywords: Closed-phase Lpc Analysis, ICASSP 2008, LPC Analysis, Signal Processing, Voice Source