  A statistical model for segmentation and word discovery in continuous speech
is presented. An incremental unsupervised learning algorithm to infer word
boundaries based on this model is described. Results of empirical tests showing
that the algorithm is competitive with other models that have been used for
similar tasks are also presented.
