Stable Audio Open
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866913453363429376 |
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| author | Evans, Zach Parker, Julian D. Carr, CJ Zukowski, Zack Taylor, Josiah Pons, Jordi |
| author_facet | Evans, Zach Parker, Julian D. Carr, CJ Zukowski, Zack Taylor, Josiah Pons, Jordi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_14358 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Stable Audio Open Evans, Zach Parker, Julian D. Carr, CJ Zukowski, Zack Taylor, Josiah Pons, Jordi Sound Artificial Intelligence Audio and Speech Processing 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. |
| title | Stable Audio Open |
| topic | Sound Artificial Intelligence Audio and Speech Processing |
| url | https://arxiv.org/abs/2407.14358 |