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--- |
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license: apache-2.0 |
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language: |
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- en |
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tags: |
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- ai |
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- rvc |
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- vc |
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- voice-cloning |
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- applio |
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- titan |
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- pretrained |
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datasets: |
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- blaise-tk/TITAN-Medium |
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pipeline_tag: audio-to-audio |
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--- |
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# TITAN: A Versatile, Robust, and High-Quality Pretrained Model for Retrieval-based Voice Conversion (RVC) Training |
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## Overview |
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TITAN is a state-of-the-art pretrained model designed for Retrieval-based Voice Conversion (https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/) training. It offers a robust solution for transforming voice characteristics from one speaker to another, providing high-quality results with minimal training effort. |
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## Model Details |
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### Titan-Medium |
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- Training Environment: Utilized a RTX 3060 TI on Applio v3.1.1 (https://github.com/IAHispano/Applio), employing a batch size of 8 over a span of 3 weeks. |
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- Iterations: X Steps |
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- Epochs: X |
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- Sampling rate: 40k, 32k (still training) |
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- Fine-tuning Process: RVC v2 pretrained with pitch guidance, leveraging an 11.15-hour dataset sourced from Expresso (https://arxiv.org/abs/2308.05725) also available on [datasets/blaise-tk/TITAN-Medium](https://huggingface.co/datasets/blaise-tk/TITAN-Medium). |
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### Titan-Large |
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- Details forthcoming... |
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## Collaborators |
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We appreciate the contributions of our collaborators who have helped in the development and refinement of TITAN. |
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- Mustar |
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- SimplCup |
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## Beta Testers |
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We extend our gratitude to the beta testers who provided valuable feedback during the testing phase of TITAN. |
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- SimplCup |
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- Leo_Frixi |
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- Light |
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- SCRFilms |
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## Citation |
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Should you find TITAN beneficial for your research endeavors or projects, we kindly request citing our repository: |
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``` |
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@article{titan, |
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title={TITAN: A Versatile, Robust, and High-Quality Pretrained Model for Retrieval-based Voice Conversion (RVC) Training}, |
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author={Blaise}, |
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journal={Hugging Face}, |
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year={2024}, |
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publisher={Blaise}, |
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url={https://huggingface.co/blaise-tk/TITAN/} |
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} |
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``` |
