This article is concerned with the question of how listeners recognize coarticulated phonemes. The problem is approached from a pattern classificationperspective. First, the potential acoustical effects
of coarticulation are defined in terms of the patterns that form the input to a classifier.Next, a categorization model called HICAT is introduced that incorporates hierarchical dependencies to optimally
dealwith this input. The model allows the position, orientation, and steepness of one phoneme boundary to depend on the perceivedvalue of a neighboring phoneme. It is argued that, if listeners do behave
like statistical pattern recognizers, they may use the categorization strategies incorporated in the model. The HICAT model is compared with existing categorizationmodels, among which are the fuzzylogical model of perception and Nearey’s diphone-biased secondary-cuemodel. Finally, a method is presented
by which categorization strategies that are likely to be used by listeners can be predicted from distributions of acoustical cues as they occur in natural speech.