Tampering Detection in Speech Signals by Semi-Fragile Watermarking Based on Singular-Spectrum Analysis

To solve the problem of unauthorized modification in speech signals, this paper proposes a novel speech-tampering-detection scheme by using the semi-fragile watermarking based on the singular-spectrum analysis (SSA). The SSA is used to analyze the speech signals of which the singular spectra are extracted. The watermark (e.g., signature information) is embedded into those signals by modifying some parts of the singular spectra according to the watermark bit. By comparing the extracted watermark with the original one, the tampered segments of the speech signals are identified and located. The evaluation results show that the proposed scheme is fragile to several malicious attacks but robust against other signal-processing operations. It also satisfies the inaudibility criteria. The proposed scheme not only can locate the tampered locations, but it also can make a prediction about the tampering types and the tampering strength.