Original Authors : Jesse Engel, Lamtharn (Hanoi) Hantrakul, Chenjie Gu, Adam Roberts (Google)
This Repository is NOT an official implement of authors.
- Clone this repository
git clone https://github.com/sweetcocoa/ddsp-pytorch
- Prepare your own audio data. (wav, mp3, flac.. )
- Use ffmpeg to convert that audio's sampling rate to 16k
# example
ffmpeg -y -loglevel fatal -i $input_file -ac 1 -ar 16000 $output_file
- Use CREPE to precalculate the fundamental frequency of the audio.
# example
crepe directory-to-audio/ --output directory-to-audio/f0_0.004/ --viterbi --step-size 4
- MAKE config file. (See configuration config/violin.yaml to make appropriate config file.) And edit train/train.py
config = setup(default_config="../configs/your_config.yaml")
- Run train/train.py
cd train
python train.py
cd train
python test.py\
--input input.wav\
--output output.wav\
--ckpt trained_weight.pth\
--config config/your-config.yaml\
--wave_length 16000
- Jongho Choi ([email protected], BS Student @ Seoul National Univ.)
- Sungho Lee ([email protected], BS Student @ Postech.)
Equally contributed.