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FFTNet

a TensorFlow implementation of the FFTNet

Quick Start

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"

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azraelkuan / FFTNet

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FFTNet

Quick Start