mlsanityData to 14 Oct 2026

Speech watermarking: an approach for the forensic analysis of digital telephonic recordings

arXiv 2203.02275 ↗First posted 23 Feb 2022cs.CR cs.LG cs.SDcited by 1

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Abstract (arXiv)

In this article, the authors discuss the problem of forensic authentication of digital audio recordings. Although forensic audio has been addressed in several articles, the existing approaches are focused on analog magnetic recordings, which are less prevalent because of the large amount of digital recorders available on the market (optical, solid state, hard disks, etc.). An approach based on digital signal processing that consists of spread spectrum techniques for speech watermarking is presented. This approach presents the advantage that the authentication is based on the signal itself rather than the recording format. Thus, it is valid for usual recording devices in police-controlled telephone intercepts. In addition, our proposal allows for the introduction of relevant information such as the recording date and time and all the relevant data (this is not always possible with classical systems). Our experimental results reveal that the speech watermarking procedure does not interfere in a significant way with the posterior forensic speaker identification.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 0 of its 22 references that are in the map. First posted on arXiv 23 Feb 2022.

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  1. 2023WavMark: Watermarking for Audio Generation
  2. 2025SpeechVerifier: Robust Acoustic Fingerprint against Tampering Attacks via Watermarking
  3. 2025The Impact of Audio Watermarking on Audio Anti-Spoofing Countermeasures
  4. 2026Feature-Aligned Speech Watermarking for Robustness to Reconstruction Distortions
  5. 2024AudioMarkBench: Benchmarking Robustness of Audio Watermarking
  6. 2025Traceable TTS: Toward Watermark-Free TTS with Strong Traceability
  7. 2026Asymmetric Phase Coding Audio Watermarking ↗
  8. 2025Smark: A Watermark for Text-to-Speech Diffusion Models via Discrete Wavelet Transform