A speech signal processing library with emphasis on deep learning.
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-compatible interface (similar to torchvision) for batch processing
- A command-line interface with a unix-pipe-like syntax
- I/O utilities for interfacing with CMUSPHINX
Some use cases of audlib are:
- Extracting common speech features for your backend
- Integrating CMUSPHINX with modern deep learning architectures
- 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's convention.
pip install audlib
In the source directory, install the library with test dependencies:
pip install ".[tests]"
python -m pytest tests
- Bump version in setup.py.
- Package release:
python setup.py sdist bdist_wheel
- Upload release:
twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
More extensive examples can be found in
- Work in progress
- First release on PyPI
Raymond Xia - email@example.com
Mahmoud Alismail - firstname.lastname@example.org
Shangwu Yao - email@example.com
Andrew Wu - firstname.lastname@example.org
Feel free to send us any issue you find and question you have.
Please contact one of the authors.
Distributed under the MIT license. See
LICENSE for more information.
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