The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


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.
User
Notifications
Font Size