pix2pix

Description

• This is a Tensorflow implementaion of Audio source separation (mixture to vocal) using the pix2pix. I pre-processed raw data(mixture and vocal pair dataset) to spectrogram that can be treated as 2-dimensional image, then train the model. See the file hyperparams.py for the detailed hyperparameters.

Requirements

• NumPy >= 1.11.1
• TensorFlow >= 1.0.0
• librosa

Data

I used DSD100 dataset which consists of pairs of mixture audio files and vocal audio files. The complete dataset (~14 GB) can be downloaded here.

File description

• hyperparams.py includes all hyper parameters that are needed.
• data.py loads training data and preprocess it into units of raw data sequences.
• modules.py contains all methods, building blocks and skip connections for networks.
• networks.py builds networks.
• train.py is for training.

Training the network

• STEP 1. Adjust hyper parameters in hyperparams.py if necessary.
• STEP 2. Download and extract DSD100 data as mentioned above at 'data' directory, and run data.py.
• STEP 3. Run train.py.

Notes

• I didn't implement evaluation code yet, but i will update soon.