Metadata-Version: 2.1
Name: audlib
Version: 0.0.3.4
Summary: A speech signal processing library with emphasis on deep learning.
Home-page: https://github.com/raymondxyy/pyaudlib
Author: Raymond Xia
Author-email: raymondxia@cmu.edu
License: MIT
Download-URL: https://github.com/raymondxyy/pyaudlib/archive/v_01.tar.gz
Keywords: SPEECH,AUDIO,SIGNAL,SOUND,DEEP LEARNING,NEURAL NETWORKS
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Multimedia :: Sound/Audio :: Analysis
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: click (>=7.0)
Requires-Dist: numpy (>=1.17.2)
Requires-Dist: soundfile (>=0.10.2)
Requires-Dist: scipy (>=1.3.1)
Requires-Dist: resampy (>=0.2.2)
Provides-Extra: display
Requires-Dist: matplotlib (>=3.1.1) ; extra == 'display'
Provides-Extra: nn
Requires-Dist: torch (>=1.2.0) ; extra == 'nn'
Requires-Dist: torchvision (>=0.4.0) ; extra == 'nn'
Provides-Extra: tests
Requires-Dist: pytest (>=5.1.3) ; extra == 'tests'
Requires-Dist: pytest-cov (>=2.8.1) ; extra == 'tests'
Requires-Dist: codecov (>=2.0.15) ; extra == 'tests'

# audlib

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> A speech signal processing library in Python with emphasis on deep learning.

audlib provides a collection of utilities for developing speech-related applications using both signal processing and deep learning. The package offers the following high-level features:

- Speech signal processing utilities with ready-to-use applications
- Deep learning architectures for speech processing tasks in [PyTorch][pytorch]
- PyTorch-compatible interface (similar to torchvision) for batch processing
- A command-line interface with a unix-pipe-like syntax

Some use cases of audlib are:

- Extracting common speech features for your backend
- Developing your own deep-learning-based tools for speech tasks
- Quickly try out speech processors and visualize the spectrogram in command line

audlib focuses on correctness, efficiency, and simplicity. Signal processing functionalities are mathematically checked whenever possible (e.g. constant overlap-add, `istft(stft(X))==X`). Deep neural networks follow the [PyTorch][pytorch]'s convention.

## Breaking Changes

- 0.0.3
  - `nn.strfnet` is removed. See the official repository [here](https://github.com/raymondxyy/strfnet-IS2020).
  - `transform.stlogm` is removed
- 0.0.2
  - `audioread` follows the interface of `soundfile.read`
  - `audiowrite` follows the interface of `soundfile.write`
  - The argument `sr` is removed from all short-time transforms

## Installation

```sh
pip install audlib
```

## Developer Installation

In the source directory, install the library with test dependencies:

```sh
pip install ".[tests]"
```

Run test:

```sh
python -m pytest tests
```

## Release flow

1. Bump version in setup.py.
2. Package release: `python setup.py sdist bdist_wheel`
3. Upload release: `twine upload --repository-url https://upload.pypi.org/legacy/ dist/*`

## Usage example

More extensive examples can be found in `examples/`.

## Release history

- 0.0.3
  - First release of the command-line tool *audpipe*
- 0.0.2
  - Streamlines optional installation
  - Improves API (**see breaking changes**)
  - Adds coverage test
- 0.0.1
  - First release on PyPI

## Contact 

Please reach out to Raymond Xia (raymondxia@cmu.edu) for comments.

More information about our research groups can be found on at

- [CMU Robust Speech Recognition Group](http://www.cs.cmu.edu/~robust/)
- [Machine Learning for Signal Processing Group](http://mlsp.cs.cmu.edu/)

## License

Distributed under the MIT license. See ``LICENSE`` for more information.

[pytorch]: https://pytorch.org/


