A comparison of different clustering algorithms for speech recognition

K-means and SOM have been frequently applied to clustering problems in speech recognition. Recently, new clustering algorithms have been introduced which present certain advantages over both of them. The present paper compares the performance of one of these, STVQ, to k-means and SOM on two well-known speech data sets.