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Custom Local Training GUI is moved to DiffTrainer


DiffSinger training notebook: Open In Colab

current supported data format:

  • lab + wav (NNSVS format)
  • csv + wav (DiffSinger format)
  • ds (DiffSinger .ds files)

NOTE:

  • your_speaker_folder's folder name will be used as spk_name so please be careful about your file naming
  • colab notebook primarily uses python; thus space in file name or folder path may be invalid
  • for an in-depth guide for SVS training and/or labeling, please see SVS Singing Voice Database - Tutorial
  • it is advised to edit your data using SlurCutter for a more refined data for your pitch model
  • please visit DiffSinger Discord for any help and questions regarding model production

Zip file format examples:

[NOTE] .ds training has the same zip organization as lab + wav, but with only .ds files- no wav needed
#single speaker (lab + wav)
your_zip.zip:
    |
    |
    your_speaker_folder:
        |
        |
        data_1.wav
        data_1.lab
        .
        data_2.wav
        data_2.lab
        .
        data_3.wav
        data_3.lab
        .
        ...
#single speaker (csv + wav)
your_zip.zip:
    |
    |
    your_speaker_folder:
        |
        |
        wavs (folder named "wavs" containing all the wavs)
        .
        transcriptions.csv
#multi speaker (lab + wav)
your_zip.zip:
    |
    |
    your_speaker_folder_1:
        |
        |
        data_1.wav
        data_1.lab
        .
        data_2.wav
        data_2.lab
        .
        data_3.wav
        data_3.lab
        .
        ...
    your_speaker_folder_2:
        |
        |
        data_1.wav
        data_1.lab
        .
        data_2.wav
        data_2.lab
        .
        data_3.wav
        data_3.lab
        .
        ...
#multi speaker (csv + wav)
your_zip.zip:
    |
    |
    your_speaker_folder_1:
        |
        |
        wavs (folder named "wavs" containing all the wavs)
        .
        transcriptions.csv
    your_speaker_folder_2:
        |
        |
        wavs (folder named "wavs" containing all the wavs)
        .
        transcriptions.csv


Vocoder finetuning notebook: Open In Colab

current supported data format:

  • wav

NOTE:

  • it is suggested to use manual segmented audio for cleaner segments (though there's minimal difference when using the auto segmentation)
  • zip file format can consist of any type of files, even subfolders. data extraction will only account .wav that are within the zip into the training set

SOFA training notebook (wip): Open In Colab

current supported data format:

  • lab + wav (NNSVS format)

NOTE:

  • this notebook is still a rough draft, please either don't use it at all or use it with caution....

Plans (update might not be in order):

  • [notebook] improve SOFA notebook, add inference
  • [script] remove the gui script and re-link to the newer gui script

Credits: