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arXiv · 2407.14358

Stable Audio Open

Zach Evans·Julian D. Parker·CJ Carr·Zack Zukowski·Josiah Taylor·Jordi Pons
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Abstract

Open generative models are vitally important for the community, allowing for fine-tunes and serving as baselines when presenting new models. However, most current text-to-audio models are private and not accessible for artists and researchers to build upon. Here we describe the architecture and training process of a new open-weights text-to-audio model trained with Creative Commons data. Our evaluation shows that the model's performance is competitive with the state-of-the-art across various metrics. Notably, the reported FDopenl3 results (measuring the realism of the generations) showcase its potential for high-quality stereo sound synthesis at 44.1kHz.

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Zach Evans, Julian D. Parker, CJ Carr, Zack Zukowski, Josiah Taylor, Jordi Pons. 2024-07-19. Stable Audio Open. https://arxiv.org/abs/2407.14358

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