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FAcodec trained on 50k hours speech data, with more timbre diversity and better at reconstructing speakers from podcasts, videos, games or animations. See main repository for example usages.
Source du modèle
Description de la source
FAcodec trained on 50k hours speech data, with more timbre diversity and better at reconstructing speakers from podcasts, videos, games or animations.
See main repository for example usages.
Sources
1 sourceVérifié 19 sept.
Artefacts du modèle
1 artefactExtraits de sources
2 extraits--- license: mit pipeline_tag: audio-to-audio --- [FAcodec](https://arxiv.org/pdf/2403.03100) trained on 50k hours speech data, with more timbre diversity and better at reconstructing speakers from podcasts, videos, games or animations. See [main repository](https://github.com/Plachtaa/FAcodec) for example usages.
Source context: 0 downloads · 10 likes · Pipeline audio-to-audio · Repo Plachta/FAcodec
