Multidirectional Local Feature for Speaker Recognition

Abstract

This paper proposes a new feature extraction method called multi-directional local feature (MDLF) to apply on an automatic speaker recognition system. To obtain MDLF, a linear regression is applied on FFT signal in four different directions which are horizontal (time axis), vertical (frequency axis), diagonal 45 degree (time-frequency) and diagonal 135 degree (time-frequency). In the experiments, Gaussian mixture model with different number of mixtures is used as classifier. Different experiments were conducted using all alphabets of Arabic for speaker recognition systems. Experimental results show that the proposed MDLF achieves better recognition accuracies than the traditional MFCC and Local features for speaker recognition system.