Fast and Effective Copy-Move Detection of Digital Audio Based on Auto Segment

Author:

Huang Xinchao1,Liu Zihan1,Lu Wei1,Liu Hongmei1,Xiang Shijun2

Affiliation:

1. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China

2. College of Information Science and Technology, Jinan University, Guangzhou, China

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.

Publisher

IGI Global

Reference21 articles.

1. Robust audio watermarking in the time domain

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3. Detecting butt-spliced edits in forensic digital audio recordings.;A. J.Cooper;39th International Conference: Audio Forensics: Practices and Challenges,2010

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5. Farid, H. (1999). Detecting digital forgeries using bispectral analysis (MIT AI Memo AIM-1657). MIT.

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