Metadata-Version: 2.1
Name: libyata
Version: 0.4.0
Summary: Yet Another Tools for Audio deep learning
Home-page: http://github.com/HudsonHuang/yata
Author: HudsonHuang
Author-email: 790209714@qq.com
License: MIT
Keywords: deep learning,audio processing,machine learning
Platform: UNKNOWN
Classifier: License :: OSI Approved :: ISC License (ISCL)
Classifier: Programming Language :: Python
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: torchaudio (>=0.3.0)
Requires-Dist: webrtcvad
Requires-Dist: fire

# yata[WIP]
Yet Another Tools for Audio deep learning(for myself).
```
pip install libyata
```
## Usage

```
import yata
```

- data augmentation
  - [x] mixup: [paper](https://arxiv.org/abs/1710.09412) [code](https://github.com/hongyi-zhang/mixup)
  - [x] SpecAugment: [paper](https://arxiv.org/abs/1904.08779) [code](https://github.com/DemisEom/SpecAugment)
  - [ ] mp3 as augumentation，用MP3编码后去掉的不可听噪声，把这种生成不可听噪声作为数据增强的手段（做法：加高斯，把MP3当成一个mask去编码，把MP3mask挖掉的区域的高斯留下来加到频谱上面，形成不可听噪声）
  - [ ] phase putertubation
- feature extraction
  - PASE: [paper](https://arxiv.org/abs/2001.09239) [code](https://github.com/santi-pdp/pase)
  - Multi scale MelSpectrogram
- Tensorflow alternatives
    - yata.utils.HParams:   
      An alternative to tf.contrib.training.HParams without Tensorflow dependency
    - yata.utils.to_categorical:   
      An alternative to tf.keras.utils.to_categorical without Tensorflow & keras dependency
- handy tools
    - yata.utils.run():  
      No more ArgumentParser!!   
      you can pass and update any parameter with:
      ```
      python test.py --a 2 --lr 0.01
      ```
      with code like:
      ```
      default_hp = {"a":1,"b":2}
      args = fyata.run(default_hp)
      print(args.a) # default_hp
      print(args.lr) # newly add from CLI
      ```
      you got:
      ```
      2
      0.01
      ```
    - yata.utils.new_dir:   
        Make directory like this `./file_a/tag/1/` with:
        ```
        new_dir("file_a", "tag", 1)
        ```
    - yata.utils.backup_code:  
        Backup all your \*.py(optional) to a zip file, eg. backup code for every experiments before running.
    - yata.utils.get_current_date: Get date as string





