Robust Copy–Move Detection of Speech Recording Using Similarities of Pitch and Formant

Abstract

Copy–move forgery on very short speech segments, followed by post-processing operations to eliminate traces of the forgery, presents a great challenge to forensic detection. In this paper, we propose a robust method for detecting and locating a speech copy–move forgery. We found that pitch and formant can be used as the features representing a voiced speech segment, and these two features are very robust against commonly used post-processing operations. In the proposed algorithm, we first divide the speech recording into voiced speech segments and unvoiced speech segments. We then extract the pitch sequence and the first two formant sequences as the feature set of each voiced speech segment. Dynamic time warping is applied to compute the similarities of each feature set. By comparing the similarities with a threshold, we can detect and locate copy–move forgeries in speech recording. The extensive experiments show that the proposed method is very effective in detecting and locating copy–move forgeries, even on a forged speech segment as short as one voiced speech segment. The proposed method is also robust against several kinds of commonly used post-processing operations and background noise, which highlights the promising potential of the proposed method as a speech copy–move forgery localization tool in practical forensics applications.