/MakeDiffSinger

Pipelines and tools to build your own DiffSinger dataset.

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

MakeDiffSinger

Pipelines and tools to build your own DiffSinger dataset.

For the recommended standard dataset making pipelines, see:

  • acoustic-forced-alignment: make dataset from scratch with MFA for acoustic model training
  • variance-temp-solution: temporary solution to extend acoustic datasets into variance datasets

For other useful pipelines and tools for making a dataset, welcome to raise issues or submit PRs.

DiffSinger dataset structure

  • dataset1/
    • raw/
      • wavs/
        • recording1.wav
        • recording2.wav
        • ...
      • transcriptions.csv
  • dataset2/
    • raw/
      • wavs/
        • ...
      • transcriptions.csv
  • ...

Essential tools to process and label your datasets

Dataset tools now have their own repository: dataset-tools.

There are mainly 3 components:

  • AudioSlicer: Slice your recordings into short segments
  • MinLabel: Label *.lab files containing word transcriptions for acoustic model training.
  • SlurCutter: Edit MIDI sequence in *.ds files for variance model training.