Stochastic Modelling of Knowledge Sources in Automatic Speech Recognition

This paper gives an overview over the stochastic approach in automatic speech recognition. The Bayes decision rule along with its application to the speech recognition problem is discussed. There are five topics in stochastic modelling for speech recognition that are studied in more detail: the EM algorithm, the probabilistic interpretation of neural net outputs, the method of decision trees, the leaving-one-out method for language modelling and the maximum entropy approach to language modelling.