A combination between VQ and covariance matrices for speaker recognition

Abstract

This paper presents a new algorithm for speaker recognition based on the combination between the classical Vector Quantization (VQ) and Covariance Matrix (CM) methods. The combined VQ-CM method improves the identification rates of each method alone, with comparable computational burden. It offers a straightforward procedure to obtain a model similar to GMM with full covariance matrices. Experimental results also show that it is more robust against noise than VQ or CM alone.

arXiv comment5 pages, published in 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), Salt Lake City, UT, USA