%0 Journal Article
	%A Ahmed Kamil Hasan Al-Ali and  Bouchra Senadji and  Ganesh Naik
	%D 2017
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 124, 2017
	%T Forensic Speaker Verification in Noisy Environmental by Enhancing the Speech Signal Using ICA Approach
	%U https://publications.waset.org/pdf/10006970
	%V 124
	%X We propose a system to real environmental noise and
channel mismatch for forensic speaker verification systems. This
method is based on suppressing various types of real environmental
noise by using independent component analysis (ICA) algorithm.
The enhanced speech signal is applied to mel frequency cepstral
coefficients (MFCC) or MFCC feature warping to extract the
essential characteristics of the speech signal. Channel effects are
reduced using an intermediate vector (i-vector) and probabilistic
linear discriminant analysis (PLDA) approach for classification. The
proposed algorithm is evaluated by using an Australian forensic voice
comparison database, combined with car, street and home noises
from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10
dB to 10 dB. Experimental results indicate that the MFCC feature
warping-ICA achieves a reduction in equal error rate about (48.22%,
44.66%, and 50.07%) over using MFCC feature warping when the
test speech signals are corrupted with random sessions of street, car,
and home noises at -10 dB SNR.
	%P 476 - 479