Sasegan
Self-Attention Generative Adversarial Network for Speech Enhancement using Tensorflow 2
Install / Use
/learn @nglehuy/SaseganREADME
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<p>SASEGAN</p>
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<p>Self Attention GAN for Speech Enhancement in Tensorflow 2</p>
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This is the TensorFlow 2 Version of Self-Attention Generative Adversarial Network for Speech Enhancement. These models can be converted to TFLite :smile:
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:yum: Supported Models
- SEGAN (Refer to https://github.com/santi-pdp/segan), see examples/segan
- SASEGAN (Refer to https://github.com/pquochuy/sasegan), see examples/sasegan
Setup Environment and Datasets
Install tensorflow: pip3 install tensorflow or pip3 install tf-nightly (for using tflite)
Install packages: pip3 install .
For setting up datasets, see datasets
To enable XLA, run TF_XLA_FLAGS=--tf_xla_auto_jit=2 $python_train_script
Clean up: python3 setup.py clean --all (this will remove /build contents)
Training & Testing
Example YAML Config Structure
speech_config: ...
model_config: ...
decoder_config: ...
learning_config:
augmentations: ...
dataset_config:
train_paths: ...
eval_paths: ...
test_paths: ...
tfrecords_dir: ...
optimizer_config: ...
running_config:
batch_size: 8
num_epochs: 20
outdir: ...
log_interval_steps: 500
See examples for some running scripts.
References
@article{phan2020sasegan,
title={Self-Attention Generative Adversarial Network for Speech Enhancement},
author={H. Phan, Hu. L. Nguyen, O. Y. Chén, P. Koch, N. Q. K. Duong, I. McLoughlin, and A. Mertins},
journal={arXiv preprint arXiv:2010.09132},
year={2020}
}
Contact
Huy Le Nguyen
Email: nlhuy.cs.16@gmail.com
