Speaker Recognition System Based on Mel Frequency Cepstral Coefficient and Four Features

Ali, Ashraf Tahseen; Abdullah, Hasanen; Fadhil, Mohammed Natiq

doi:10.33103/uot.ijccce.21.4.8

	Speaker Recognition System Based on Mel Frequency Cepstral Coefficient and Four Features
IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING
Article 8, Volume 21, Issue 4, 2021, Pages 82-89 PDF (610.25 K)
Document Type: Research Paper
DOI: 10.33103/uot.ijccce.21.4.8
Authors
Ashraf Tahseen Ali^* ¹; Hasanen Abdullah²; Mohammed Natiq Fadhil³
¹Unversity of Technology
²Computer Sciences Department University of Technology Baghdad Iraq
³Computer Sciences Department, University of Technology, Baghdad, Iraq
Abstract
Biometrics signs are the most important factor in the human recognition field and considered an effective technique for person authentication systems. Voice recognition is a popular method to use due to its ease of implementation and acceptable effectiveness. This research paper will introduce a speaker recognition system that consists of preprocessing techniques to eliminate noise and make the sound smoother. For the feature extraction stage, the method Mel Frequency Cepstral Coefficient (MFCC) is used, and in the second step, the four features (FF) Mean, Standard Division, Zero-Cross and Amplitude, which added to (MFCC) to improve the results. For data representation, vector quantization has been used. The evaluation method (k-fold cross-validation) has been used. Supervised machine learning (SML) is proposed using Quadratic Discriminant Analysis (QDA) classification algorithms. And the results obtained by the algorithm (QDA) varied between 98 percent and 98.43 percent, depending on the way of features extraction that was used. These results are satisfactory and reliable.
Keywords
SML; QDA; Voice Recognition; MFCC; FF

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