Joint Distributional Modeling with Cross-Correlation Based Features

Abstract

In maximum-likelihood based speech recognition systems, it is important to accurately estimate the joint distribution of feature vectors given a particular acoustic model. In this work, we propose that by modeling the joint distribution of time-localized feature vectors and statistics relating those time-localized feature vectors to the relevant acoustic… (More)

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