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New TTS watermarking framework GAMW enhances speech traceability

Researchers have developed GAMW, a novel framework for embedding imperceptible watermarks into synthesized speech during the text-to-speech (TTS) generation process. This method, detailed in an arXiv paper, embeds a content-adaptive multi-bit watermark residual before waveform synthesis. GAMW demonstrates improved decoding accuracy over existing methods, particularly under various perturbations, while maintaining high speech quality. AI

IMPACT Enhances security and traceability for synthesized speech, potentially impacting content moderation and verification systems.

RANK_REASON The cluster contains an academic paper detailing a new technical method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New TTS watermarking framework GAMW enhances speech traceability

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The cluster contains an academic paper detailing a new technical method. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yihang Zhang, Weicai Yan, Qifei Zhang, Yangyang Wu, Tao Jin ·

    GAMW: Generation-Aware Mel-Domain Watermarking for TTS Traceability

    arXiv:2610.15082v1 Announce Type: cross Abstract: As text-to-speech (TTS) systems continue to advance, provenance tracking and security verification of synthesized speech have become increasingly important. Audio watermarking provides active provenance by embedding imperceptible,…