Speech recognition features based on deep latent Gaussian models

This paper constructs speech features based on a generative model using a deep latent Gaussian model (DLGM), which is trained using stochastic gradient variational Bayes (SGVB) algorithm and performs efficient approximate inference and learning with a directed probabilistic graphical model. The trained DLGM then generate latent variables based on Gaussian… CONTINUE READING