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Technique-Controllable SVS

This is a referenc version, please use TCSinger for better technique control!

Data Preparation

  1. Downlowad GTSinger and process all json to metadata.json.
  2. Put metadata.json (including ph, word, item_name, ph_durs, tech,mix_tech, falsetto_tech, breathy_tech, pharyngeal_tech, vibrato_tech, glissando_tech, wav_fn, singer, ep_pitches, ep_notedurs, ep_types for each singing voice), spker_set.json (including all singers and their id), and phone_set.json (all phonemes of your dictionary) in data/processed/style
  3. Set processed_data_dir, binary_data_dir,valid_prefixes, test_prefixes in the config.
  4. Preprocess Dataset
export PYTHONPATH=.
CUDA_VISIBLE_DEVICES=$GPU python data_gen/tts/bin/binarize.py --config egs/stylesinger.yaml

Training StyleSinger

CUDA_VISIBLE_DEVICES=$GPU python tasks/run.py --config egs/stylesinger.yaml  --exp_name StyleSinger --reset

Inference using StyleSinger

CUDA_VISIBLE_DEVICES=$GPU python tasks/run.py --config egs/stylesinger.yaml  --exp_name StyleSinger --infer

Acknowledgements

This implementation uses parts of the code from the following Github repos: StyleSinger as described in our code.