Paper Info
Title
A Novel Arabic Text-independent Speaker Verification System based on Fuzzy Hidden Markov Model.
Abstract
The most important shortcoming of the current speaker verification methods (based on knowledge or possession) is that this process is not sure whether the holder of the given ID is the entitled one or an imposter. Using biometrics in the verification system is designated for minimizing this problem and decreasing the necessity of carrying the tokens. In this paper, a novel Arabic text-independent speaker verification system is presented. First of all, new speech features are proposed for speaker characterization, which denoted as Wavelet Packet Four-Directional Features (WPFDF). With the objective of speaker verification, the paper proposes a Fuzzy Hidden Markov Model, termed FHMM, where the kernel fuzzy c-means (KFCM) is extended to calculate fuzzy memberships of HMMs training samples. Thus, information loss is reduced as well as recognition rate is increased. The proposed approach reached 98.38% of recognition rate.
Year
DOI
Venue
2017
10.1016/j.procs.2017.10.119
Procedia Computer Science
Keywords
Field
DocType
Speech recognition,Arabic text-independent speaker verification,Wavelet packet-four directional features,FHMM
Kernel (linear algebra),Pattern recognition,Computer science,Network packet,Fuzzy logic,Speech recognition,Speaker recognition,Artificial intelligence,Speaker diarisation,Biometrics,Hidden Markov model,Wavelet
Conference
Volume
ISSN
Citations 
117
1877-0509
0
PageRank 
References 
Authors
0.34
15
2
Name
Order
Citations
PageRank
Rania M. Ghoniem101.01
Khaled F. Shaalan250639.80