Detection algorithm of electronic disguised voice based on convolutional neural network
An electronic disguised voice detection algorithm based on the statistical features of MFCC and the convolution neural network was proposed.Firstly,the statistical features of MFCC were extracted and reconstructed as the input of convolution neural network.Considering the convolution kernel size,the...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2018-02-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018041/ |
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| _version_ | 1841530301902225408 |
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| author | Hongwei XU Diqun YAN Fan YANG Rangding WANG Chao JIN Li XIANG |
| author_facet | Hongwei XU Diqun YAN Fan YANG Rangding WANG Chao JIN Li XIANG |
| author_sort | Hongwei XU |
| collection | DOAJ |
| description | An electronic disguised voice detection algorithm based on the statistical features of MFCC and the convolution neural network was proposed.Firstly,the statistical features of MFCC were extracted and reconstructed as the input of convolution neural network.Considering the convolution kernel size,the number of convolution kernels and the pooling size,24 different network structures were evaluated in this work.Finally,the convolution neural network structure which could be effectively used for electronic disguised voice detection was determined.The experimental results show that the proposed algorithm can effectively detect the trace of electronic disguising.Meanwhile,the specific forgery operation of the electronic disguised voice can also be estimated. |
| format | Article |
| id | doaj-art-8cee86ce6b354df68710f2e7673938c7 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2018-02-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-8cee86ce6b354df68710f2e7673938c72025-01-15T03:05:11ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012018-02-0134465759596963Detection algorithm of electronic disguised voice based on convolutional neural networkHongwei XUDiqun YANFan YANGRangding WANGChao JINLi XIANGAn electronic disguised voice detection algorithm based on the statistical features of MFCC and the convolution neural network was proposed.Firstly,the statistical features of MFCC were extracted and reconstructed as the input of convolution neural network.Considering the convolution kernel size,the number of convolution kernels and the pooling size,24 different network structures were evaluated in this work.Finally,the convolution neural network structure which could be effectively used for electronic disguised voice detection was determined.The experimental results show that the proposed algorithm can effectively detect the trace of electronic disguising.Meanwhile,the specific forgery operation of the electronic disguised voice can also be estimated.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018041/electronic disguised voiceconvolutional neural networkMFCC |
| spellingShingle | Hongwei XU Diqun YAN Fan YANG Rangding WANG Chao JIN Li XIANG Detection algorithm of electronic disguised voice based on convolutional neural network Dianxin kexue electronic disguised voice convolutional neural network MFCC |
| title | Detection algorithm of electronic disguised voice based on convolutional neural network |
| title_full | Detection algorithm of electronic disguised voice based on convolutional neural network |
| title_fullStr | Detection algorithm of electronic disguised voice based on convolutional neural network |
| title_full_unstemmed | Detection algorithm of electronic disguised voice based on convolutional neural network |
| title_short | Detection algorithm of electronic disguised voice based on convolutional neural network |
| title_sort | detection algorithm of electronic disguised voice based on convolutional neural network |
| topic | electronic disguised voice convolutional neural network MFCC |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018041/ |
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