AudioSeal We introduce AudioSeal, a method for speech localized watermarking, with state of the art robustness and detector speed. It jointly trains a generator that embeds a watermark in the audio, and a detector that detects the watermarked fragments in longer audios, even in the presence of editing. Audioseal achieves state of the art detection performance of both natural and synthetic speech at the sample level (1/16k second resolution), it generates limited alteration of signal quality and is robust to many types of audio editing. 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. 🧉 Installation AudioSeal requires Python =3.8, Pytorch = 1.13.0, omegaconf, julius, and numpy. To install from PyPI: To install from source: Clone this repo and install in editable mode: ⚙️ Models We provide the checkpoints for the following models: AudioSeal Generator. It takes as input an audio signal (as a waveform), and outputs a watermark of the same size as the input, that can be added to the input to watermark it. O…
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