Supervector

A supervector is a high-dimensional feature representation created by concatenating the mean vectors from all components of a Gaussian Mixture Model (GMM) adapted to a specific speaker or utterance. This concatenation transforms variable-length speech into a fixed-length vector suitable for machine learning classifiers. In accessibility research, supervectors have been used for dysarthric speech analysis, intelligibility assessment, and speaker characterization. While effective, supervectors have been largely superseded by iVectors, which offer similar discriminative power in a much lower-dimensional space.