Context dependent modeling of phones in continuous speech using decision trees

In a continuous speech recognition system it is important to model the context dependent variations in the pronunciations of words. In this paper we present an automatic method for modeling phonological variation using decision trees. For each phone we construct a decision tree that specifies the acoustic realization of the phone as a function of the context in which it appears. Several thousand sentences from a natural language corpus spoken by several talkers are used to construct these decision trees. Experimental results on a 5000-word vocabulary natural language speech recognition task are presented.