A Study on Speaker Recognition Using Orthogonal Gaussian Mixture Models
Hou Feng · Journal of Information Engineering University · 2002
This paper introduces the Orthogonal Gaussian mixture model (OGMM) and the application in the speaker recognition Standard GMM assumes diagonal covariance matrices, and needs a large number of mixture components to obtain good approximation which leads to greater training time. This paper proposes a modification to the standard diagonal GMM approach: feature vectors are first transformed to the space spanned by the eigenvectors of the covariance matrix before being applied to the diagonal GMM. An OGMM based speaker recognition experiments show that the performance is better than the standard GMM and has better prospects.