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岁己SUI的sovits底模数据集
Dataset Summary
ForBaseModel.zip:
数据质量不高,只用于岁己音色的底模训练(洗去G_0.pth和D_0.pth的音色)
采样频率为44.1kHz,使用前请注意预处理
取自岁己22年12月、23年1月的录播(除电台,共计211:13:21),经过以下步骤筛选处理
挑取BGM音量较低的直播片段(20:39:21)_[LowBGM.zip]
UVR5 VR Architecture 5_HP-Karaoke-UVR统一处理,尽量除去了BGM中的人声(20:39:20,反正确实就是少了1s)_[UVR-ed.zip]
Audio Slicer切片(12:45:29)_[Slice-d.zip]
Fish Audio Preprocessor响度标准化并删除过短过长的片段(11:24:06)_[LoudnessNorm-ed.zip]
Spliter Wav by IceKyrin声纹识别稳定数据(06:47:46)_[ForBaseModel.zip]
文件结构:
ForBaseModel.zip
├── 25788785-20221201-195959-658_01_(Vocals)_1.wav
├── 25788785-20221201-195959-658_01_(Vocals)_3.wav
├── ......
├── 25788785-20230201-005152-235_03_(Vocals)_9.wav
└── 25788785-20230201-005152-235_03_(Vocals)_10.wav
ForBaseModel_sovits3.0.zip:
ForBaseModel.zip经过预处理后的数据集,可以直接投入sovits3.0_48k使用,采样频率为48kHz
文件结构:
ForBaseModel_sovits3.0.zip
├── configs
│ └── config.json
├── dataset
│ └── 48k
│ └── suijiSUI
│ ├── 25788785-20221201-195959-658_01_(Vocals)_1.wav
│ ├── 25788785-20221201-195959-658_01_(Vocals)_1.wav.f0.npy
│ ├── 25788785-20221201-195959-658_01_(Vocals)_1.wav.soft.pt
│ ├── ......
│ ├── 25788785-20230201-005152-235_03_(Vocals)_10.wav
│ ├── 25788785-20230201-005152-235_03_(Vocals)_10.wav.f0.npy
│ └── 25788785-20230201-005152-235_03_(Vocals)_10.wav.soft.pt
└── filelists
├── test.txt
├── train.txt
└── val.txt
ForBaseModel_sovits4.0.zip:
ForBaseModel.zip经过预处理后的数据集,可以直接投入sovits4.0使用,采样频率为44.1kHz
注意:4.0开始config.json中的batch_size默认为6,我又给改回12了
文件结构:
ForBaseModel_sovits4.0.zip
├── configs
│ └── config.json
├── dataset
│ └── 44k
│ └── suijiSUI
│ ├── 25788785-20221201-195959-658_01_(Vocals)_1.wav
│ ├── 25788785-20221201-195959-658_01_(Vocals)_1.wav.f0.npy
│ ├── 25788785-20221201-195959-658_01_(Vocals)_1.wav.soft.pt
│ ├── ......
│ ├── 25788785-20230201-005152-235_03_(Vocals)_10.wav
│ ├── 25788785-20230201-005152-235_03_(Vocals)_10.wav.f0.npy
│ └── 25788785-20230201-005152-235_03_(Vocals)_10.wav.soft.pt
└── filelists
├── test.txt
├── train.txt
└── val.txt
Supported Tasks and Leaderboards
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Languages
Chinese(98%)
English(1%)
Japanese(1%)
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Dataset Structure
Data Instances
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Data Fields
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Data Splits
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Dataset Creation
Curation Rationale
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Source Data
Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Social Impact of Dataset
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