AIRCC's International Journal of Computer Science and Information Technology

R. L. K. Venkateswarlu ¹, R. Vasantha Kumari ², A. K. V. Nagayya ¹

Affiliations
1 Department of Information Technology, Sasi Institute of Technology and Engineering, Tadepalligudem, IN
2 Perunthalaivar Kamarajar Arts College, Puducherry 605 107, IN

Abstract

The method of self-organizing maps (SOM) is a method of exploratory data analysis used for clustering and projecting multi-dimensional data into a lower-dimensional space to reveal hidden structure of the data. The Self-Organizing Feature Maps (SOFMs) [11] is a class of neural networks capable of recognizing the main features of the data they are trained on. There is extensive literature on its biological and mathematical concepts and even more on its implementation in a variety of areas including medicine, finance, chaos and data mining in general [4,2]. The aim of this research is to implement a self-organizing neural network based technique for speech recognition. The Mean-SOM performance for the feature Intensity is obtained maximum as 98.17%. The Median-SOM performance for the feature Intensity is obtained maximum as 98.54%.

Keywords

Self-Organized Map, Artificial Neural Networks, Feature, Mean-SOM Performance, Median-SOM Performance, LPCC, MFCC, Pitch, Intensity, Hits, Cycles, Iterations.

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