title: Proactive Detection of Voice Cloning with Localized Watermarking
summary: In the rapidly evolving field of speech generative models, there is a
  pressing need to ensure audio authenticity against the risks of voice cloning.
  We present AudioSeal, the first audio watermarking technique designed
  specifically for localized detection of AI-generated speech. AudioSeal employs
  a generator/detector architecture trained jointly with a localization loss to
  enable localized watermark detection up to the sample level, and a novel
  perceptual loss inspired by auditory masking, that enables AudioSeal to achieve
  better imperceptibility. AudioSeal achieves state-of-the-art performance in
  terms of robustness to real life audio manipulations and imperceptibility based
  on automatic and human evaluation metrics. Additionally, AudioSeal is designed
  with a fast, single-pass detector, that significantly surpasses existing models
  in speed - achieving detection up to two orders of magnitude faster, making it
  ideal for large-scale and real-time applications.
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paper_authors.name: Robin San Roman
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paper_authors.fullname: Robin San Roman
paper_authors.type: user
paper_authors.user: Sparker17
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paper_authors.name: Pierre Fernandez
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paper_authors.fullname: Pierre Fernandez
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paper_authors.user: pierrefdz
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paper_authors.name: Alexandre Défossez
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paper_authors.fullname: Alexandre Défossez
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paper_authors.user: adefossez
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paper_authors.name: Teddy Furon
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paper_authors.fullname: Teddy Furon
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paper_authors.user: tfuron
paper_authors._id: 65b9cf6dd88a65abb9117e6e
paper_authors.name: Tuan Tran
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paper_authors.fullname: Tuan Tran
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paper_authors.user: tuantran
paper_authors._id: 65b9cf6dd88a65abb9117e6f
paper_authors.name: Hady Elsahar
paper_authors.status: admin_assigned
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paper_authors._id: 60338cdfb5883695ce9d0916
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/60338cdfb5883695ce9d0916/BXbJKt_UwoFnh7xB4ewHs.jpeg
paper_authors.fullname: Hady Elsahar
paper_authors.type: user
paper_authors.user: hadyelsahar
paper_title: Proactive Detection of Voice Cloning with Localized Watermarking
paper_summary: In the rapidly evolving field of speech generative models, there is a
  pressing need to ensure audio authenticity against the risks of voice cloning.
  We present AudioSeal, the first audio watermarking technique designed
  specifically for localized detection of AI-generated speech. AudioSeal employs
  a generator/detector architecture trained jointly with a localization loss to
  enable localized watermark detection up to the sample level, and a novel
  perceptual loss inspired by auditory masking, that enables AudioSeal to achieve
  better imperceptibility. AudioSeal achieves state-of-the-art performance in
  terms of robustness to real life audio manipulations and imperceptibility based
  on automatic and human evaluation metrics. Additionally, AudioSeal is designed
  with a fast, single-pass detector, that significantly surpasses existing models
  in speed - achieving detection up to two orders of magnitude faster, making it
  ideal for large-scale and real-time applications.
paper_ai_summary: AudioSeal is an audio watermarking technique that uses a generator/detector architecture to detect AI-generated speech with high robustness and imperceptibility, offering fast detection.
paper_ai_keywords: generator/detector architecture localization loss perceptual loss auditory masking state-of-the-art robustness imperceptibility automatic evaluation human evaluation single-pass detector real-time applications