This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in the context of linear inverse problems with additive noise. We fit GMM to given samples obtain an analytic probability density function (PDF) which approximates true PDF. Then, conditional mean (CME) corresponding this approximating PDF is computed closed form and used as approximation optimal CME cannot be c...

The primary goal of this master thesis project is to implement a text independent speaker verification module for GIVES. Secondary goals are to implement a fast scoring method and compare performance between the implemented text independent module and an available text dependent module. The project also includes a literature study. The text independent module is based on adapted Gaussian Mixtur...