A combination between VQ and covariance matrices for speaker recognition

Presents an 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 the Gaussian model mixture method with full covariance matrices. Experimental results also show that it is more robust against noise than VQ or CM alone