Fuzzy Clustering Approach Using Data Fusion Theory and its Application To Automatic Isolated Word Recognition

Abstract

In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the proposed algorithms have better performance, compared to classical clustering.