A Statistical Model for Word Discovery in Transcribed Speech
arXiv:cs/0111065
Abstract
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.
Expanded version of ICML-01 paper (pp.569--576)