- Rita Singh. 2003. HEATING HMM STATE DENSITIES FOR SPEECH RECOGNITON. Abstract: Currently, the best performing state-of-art large vocabulary speech recognition systems are statistical pattern classifiers which model sound units using hidden Markov models (HMMs). Given a sequence of data X derived from the speech signal, the classification problem that is solved is that of finding the class c(X) for which the following expression, given by Bayes classification rule, is maximized: (1)
