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Novel approach for speech recognition by using self — Organized maps

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2 Author(s)
R. L. K. Venkateswarlu ; Department of Information Technology, Sasi Institute of Technology and Engineering, Tadepalligudem, India ; R. Vasantha Kumari

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) 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. 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%.

Published in:

Emerging Trends in Networks and Computer Communications (ETNCC), 2011 International Conference on

Date of Conference:

22-24 April 2011