. Voice Separate Models for speech application

├── README.md

├── code: core model for speech separate
    ├── __init__.py
    ├── __pycache__
    ├── conf.yml
    ├── conv_tasnet.py
    ├── data.py
    ├── dprnn-train-deploy.py
    ├── inference.py
    ├── parser_utils.py
    ├── requirements.txt
    ├── wham_dataset_no_sf.py
    └── wsj0_mix.py

├── conf.yml: config file for model

├── helper: helper function for application
    ├── __pycache__
    └── utils.py

├── local_experiment.ipynb: local experiment

├── train_and_deploy.ipynb: implementation in Sagemaker

├── mix_both.json: config for mix application

├── result: sample results
    ├── complete_split_s1.wav
    └── complete_split_s2.wav

├── split_weight: best model for speech application
    └── best_model.pth

├── test_sample: test sample for speech application
    └── audio_raw_1-20_clip_0.wav


└── train_sample_v6: sample for train/validation
    ├── cv
    ├── tr
    └── tt

11 directories, 20 files