Three-dimensional AI Clone Speech Source Identification Method Based on Improved MFCC Feature Model

The emergence of AI cloned voice technology will have a fatal impact on the legal order of modern society.In recent years, researchers have only focused on the research in the field of AI-synthesized speech containing the same sample speech content, but little research has been done on the identific...

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Bibliographic Details
Published inJi suan ji ke xue Vol. 50; no. 11; p. 177
Main Authors Wang, Xueguang, Zhu, Junwen, Zhang, Aixin
Format Journal Article
LanguageChinese
Published Chongqing Guojia Kexue Jishu Bu 01.01.2023
Subjects
Cloning
Identification methods
Mutation
Random sampling
Speech
Speech recognition
Synthesis
Three dimensional models
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Summary:The emergence of AI cloned voice technology will have a fatal impact on the legal order of modern society.In recent years, researchers have only focused on the research in the field of AI-synthesized speech containing the same sample speech content, but little research has been done on the identification of AI-synthesized speech containing the content that is different from the sample content.Thus, this paper proposes a three-dimensional model to identify AI cloned speech sources based on an improved MFCC feature model.Firstly, it verifies the characteristics of artificially analyzed AI cloned speech by previous scholars, and summarize the characteristics of "abnormally active formant F5" and "abnormal mutation of energy, formant and pitch curve" for computer identification.Secondly, it uses the second-order difference to correct the MFCC coefficients based on the characte-ristics of AI cloned speech, and use the "inverse logic deduction method" to further quantify and sample the mutation characteristics of e
ISSN:1002-137X