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doof-ferb
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rvc-ngngngan

Audio-to-Audio
TensorBoard
Vietnamese
rvc
RVC
Model card Files Metrics Community
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README.md CHANGED
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1
  ---
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  license: cc-by-nc-sa-4.0
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: cc-by-nc-sa-4.0
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+ language: vi
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+ base_model: lj1995/VoiceConversionWebUI
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+ pipeline_tag: audio-to-audio
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+ inference: false
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+ tags: [rvc, RVC]
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  ---
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+ # RVC NgNgNgan
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+
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+ ## License
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+
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+ ![license](https://mirrors.creativecommons.org/presskit/buttons/88x31/png/by-nc-sa.png)
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+
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+ In accordance with the terms of the CC-BY-NC-SA-4.0 license, the use of my checkpoints and any audio output generated by them for commercial purposes is strictly prohibited. This includes, but is not limited to:
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+ - online and offline voice cloning as a service
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+ - online and offline text-to-speech as a service
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+ - content creation for monetization on social media platforms
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+
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+
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+ Căn cứ vào các điều khoản của giấp phép CC-BY-NC-SA-4.0, việc sử dụng các checkpoints này và bất kỳ đầu ra âm thanh nào được tạo bởi chúng đều bị nghiêm cấm sử dụng cho mục đích thương mại. Điều này bao gồm, nhưng không giới hạn ở:
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+ - các dịch vụ nhân bản giọng nói trực tuyến và ngoại tuyến
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+ - các dịch vụ chuyển văn bản thành giọng nói trực tuyến và ngoại tuyến
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+ - tạo nội dung để kiếm tiền trên các nền tảng mạng xã hội
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+
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+ ## What is RVC?
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+
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+ original: https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI
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+
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+ i trained using this fork: https://github.com/IAHispano/Applio
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+
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+ ## Final result:
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+
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+ - checkpoint: https://huggingface.co/doof-ferb/rvc-ngngngan/blob/main/ckpt/nguyenngocngan_e160_s168480.pth
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+ - index: https://huggingface.co/doof-ferb/rvc-ngngngan/blob/main/idx/added_IVF256_Flat_nprobe_1_nguyenngocngan_v2.index
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+
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+ ## About this repo
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+
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+ - Vietnamese M.C. Nguyễn Ngọc Ngạn
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+ - data scraping code: https://github.com/phineas-pta/speech-synthesis-ngngngan
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+ - 6h30min audio at 48 kHz + RMVPE pitch extraction = 16.1 GiB disk space
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+ - batch size = 8 ⇒ 1 epoch = 1053 steps
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+ - train locally from scratch, ≈ 10’30” per epoch
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+ - train 300 epochs, save ckpt every 5 epoch, select ckpt at 160th epoch
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+ - i haven’t tested all the models 1 by 1
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