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Fast and Effective Copy-Move Detection of Digital Audio Based on Auto Segment
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Author(s): Xinchao Huang (School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China), Zihan Liu (School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China), Wei Lu (School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China), Hongmei Liu (School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China)and Shijun Xiang (College of Information Science and Technology, Jinan University, Guangzhou, China)
Copyright: 2020
Pages: 16
Source title:
Digital Forensics and Forensic Investigations: Breakthroughs in Research and Practice
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-3025-2.ch011
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Abstract
Detecting digital audio forgeries is a significant research focus in the field of audio forensics. In this article, the authors focus on a special form of digital audio forgery—copy-move—and propose a fast and effective method to detect doctored audios. First, the article segments the input audio data into syllables by voice activity detection and syllable detection. Second, the authors select the points in the frequency domain as feature by applying discrete Fourier transform (DFT) to each audio segment. Furthermore, this article sorts every segment according to the features and gets a sorted list of audio segments. In the end, the article merely compares one segment with some adjacent segments in the sorted list so that the time complexity is decreased. After comparisons with other state of the art methods, the results show that the proposed method can identify the authentication of the input audio and locate the forged position fast and effectively.
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