Speaker Identification Using a Combination of Different Parameters as Feature Inputs to an Artificial Neural Network Classifier

Viresh Moonasar
Ganesh K. Venayagamoorthy, Missouri University of Science and Technology

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1273

There were 22 downloads as of 27 Jun 2016.

Abstract

This paper presents a technique using artificial neural networks (ANNs) for speaker identification that results in a better success rate compared to other techniques. The technique used in this paper uses both power spectral densities (PSDs) and linear prediction coefficients (LPCs) as feature inputs to a self organizing feature map to achieve a better identification performance. Results for speaker identification with different methods are presented and compared.