Exploration of sparse representation techniques in language recognition

Abstract

The work presented in this thesis investigates different approaches for achieving efficient sparse representation for the purpose of language recognition LR task In this context both simple and discriminatively learned dictionaries have been explored employing different kinds of regularization The presented approaches are contrasted with state of the art i vector representation of speech utterance along with LDA WCCN session channel compensation based LR approach Towards addressing high co...