Feature Based Performance Evaluation of Support Vector Machine on Binary Classification

Author(s):  
Shivani Sharma ◽  
Saurabh Kr. Srivastava
2018 ◽  
Vol 7 (2.16) ◽  
pp. 98 ◽  
Author(s):  
Mahesh K. Singh ◽  
A K. Singh ◽  
Narendra Singh

This paper emphasizes an algorithm that is based on acoustic analysis of electronics disguised voice. Proposed work is given a comparative analysis of all acoustic feature and its statistical coefficients. Acoustic features are computed by Mel-frequency cepstral coefficients (MFCC) method and compare with a normal voice and disguised voice by different semitones. All acoustic features passed through the feature based classifier and detected the identification rate of all type of electronically disguised voice. There are two types of support vector machine (SVM) and decision tree (DT) classifiers are used for speaker identification in terms of classification efficiency of electronically disguised voice by different semitones.  


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 86555-86569 ◽  
Author(s):  
Sugen Chen ◽  
Junfeng Cao ◽  
Zhong Huang ◽  
Chuansheng Shen

2019 ◽  
Vol 23 (21) ◽  
pp. 10649-10659 ◽  
Author(s):  
Xiaopeng Hua ◽  
Sen Xu ◽  
Jun Gao ◽  
Shifei Ding

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