Application of Clustering Techniques to Speaker-Trained Isolated Word Recognition
L. R. Rabiner, Jay G. Wilpon · Bell System Technical Journal · 1979
Speaker-trained, isolated word recognizers have achieved notable success in a wide variety of applications. The training for such systems generally involves a single (or sometimes two) replication(s) of each word of the vocabulary by the designated talker. Word reference templates are then formed directly from these replications. In recent work on speaker-independent word recognition, it has been shown that statistical clustering procedures provided an effective way for determining the structure in multiple replications of a word by different talkers. Such techniques were then used to provide a set of reference templates based on the clustering results. In this paper we discuss the application of clustering techniques to speaker-trained word recognizers. It is shown that significant improvements in recognition accuracy are obtained when using templates obtained from a clustering analysis of multiple replications of a word by the designated talker. It is also shown that recognition accuracy did not change with time (over a 6-month period) for any of the subjects tested, thereby indicating that the reference templates were reasonably stable.