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  • 标题:Detection of Fake Voice Generated By GAN Using CVAE
  • 本地全文:下载
  • 作者:Nisarga J N ; Poornima H N ; Kavya S N
  • 期刊名称:International Journal of Advances in Engineering and Management
  • 电子版ISSN:2395-5252
  • 出版年度:2020
  • 卷号:2
  • 期号:4
  • 页码:860-865
  • DOI:10.35629/5252-0204821825
  • 语种:English
  • 出版社:IJAEM JOURNAL
  • 摘要:The advent of deep learning generative models enables realistic generation from known data distribution, such as images, videos and sounds. Voice samples generated by such models can used for malicious purposes, i.e. fraud and impersonation if one fails to detect and report them. This poses challenges on the state-of-the-art voice verification systems to identify generated fake voices in order to prevent misuse of fake information. To test established verification systems against fake voices, we obtained a dataset of fake voices by CycleGAN-VC and used it to investigate two verification systems, 1) convolutional VAE, to see if they can detect generated fake voices.
  • 关键词:Cloned Audio;Generative Adversarial Network (GAN);Mel-Frequency CepstralCoeffients (MFFCs);Convolutional VariationalAutoencoder (CVAE);Voice Verification
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