Boosting HMM performance with a memory upgrade

Abstract

The state-of-the-art in automatic speech recognition is distinctly Markovian. The ubiquitous ‘beads-on-a-string’ approach, where sentences are explained as a sequence of words, words as a sequence of phones and phones as a sequence of acoustically stable states, is bound to lose a lot of dynamic information. In this paper we show that a combination with… (More)

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