Modification of fuzzy C-means algorithm with automatic selection of the number of clusters for speech utterance categorization

In this paper we propose a fuzzy clustering algorithm, which is able to find the clusters in a data set without the number of clusters as a user input parameter. The algorithm is based on the standard fuzzy c-means method and consists of two parts: 1) detecting the number of clusters с; 2) calculating the cluster partition with the obtained с. We apply this method to the preprocessed database which was provided by Speech Cycle Company. The proposed algo rithm has been tested with optimal parameters which we have calculated on the test data.