A combination between VQ and covariance matrices for speaker recognition
Marcos Faúndez-Zanuy · 2002
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.