Abstract

Resampling is an operation to convert a digital speech from a given sampling rate to a different one. It can be used to interface two systems with different sampling rates. Unfortunately, resampling may also be intentionally utilized as a postoperation to remove the manipulated artifacts left by pitch shifting, splicing, etc. To detect the resampling, some forensic detectors have been proposed. Little consideration, however, has been given to the security of these detectors themselves. To expose weaknesses of these resampling detectors and hide the resampling artifacts, a dual‐path resampling antiforensic framework is proposed in this paper. In the proposed framework, 1D median filtering is utilized to destroy the linear correlation between the adjacent speech samples introduced by resampling on low‐frequency component. And for high‐frequency component, Gaussian white noise perturbation (GWNP) is adopted to destroy the periodic resampling traces. The experimental results show that the proposed method successfully deceives the existing resampling forensic algorithms while keeping good perceptual quality of the resampled speech.

Highlights

  • With the wide availability of powerful audio-editing tools such as Adobe Audition, Audacity, and GoldWave, one can modify a digital speech with little or no obvious perceptual artifacts

  • We focus on antiforensics of speech resampling

  • A resampling antiforensic method based on dual-path strategy is proposed to attack the existing forensic detectors

Read more

Summary

Introduction

With the wide availability of powerful audio-editing tools such as Adobe Audition, Audacity, and GoldWave, one can modify a digital speech with little or no obvious perceptual artifacts. Various speech forensic techniques have been proposed to identify different kinds of forgery, such as replaying [3, 4], pitch shifting [5, 6], and double compression [7]. Resampling is an operation widely used to convert a digital speech from a given sampling rate to a different sampling rate. It is worth noting that resampling is a necessary operation when a speech undergoes other manipulations like pitch shifting, splicing, and fake-quality mp compositing [8]. Resampling could be used as a postprocessing operation to hide the artifacts left by the forgery operations [9]

Objectives
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.