a TensorFlow implementation of the FFTNet
- install requirements
pip install -r requirements.txt
-
Download data click here
-
Extract Features
python preprocess.py \
--name cmu_arctic \
--in_dir your_data_dir \
--out_dir the_feature_dir \
--hparams "input_type=mulaw-quantize" # mulaw_quantize is better in my test
- Training Process
you can split your train.txt
into two parts in you data_dir
python train.py \
--train_file "your_data_dir/train.txt" \
--val_file "your_data_dir/val.txt" \
--name "upsample_slt"
- Synthesis Process
python synthesis.py \
--checkpoint_path "your_checkpoint_dir" \
--output "your_output_dir" \
--local_path "local_condtion_path"