Gaussian Mixture Model

A Gaussian Mixture Model (GMM) is a probabilistic model that represents data as a weighted combination of multiple Gaussian (normal) distributions. Each component Gaussian has its own mean and covariance, allowing GMMs to model complex, multimodal distributions. In speech technology and accessibility applications, GMMs are widely used for acoustic modeling in speech recognition, speaker identification, and dysarthric speech analysis. They form the basis for more advanced techniques like Universal Background Models and supervectors used in intelligibility assessment systems for people with speech impairments.