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A speech signal processing library with emphasis on deep learning.

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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-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.

Breaking Changes

  • 0.0.3
    • transform.stlogm is removed
  • 0.0.2
    • audioread follows the interface of
    • audiowrite follows the interface of soundfile.write
    • The argument sr is removed from all short-time transforms


pip install audlib

Developer Installation

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

pip install ".[tests]"

Run test:

python -m pytest tests

Release flow

  1. Bump version in
  2. Package release: python sdist bdist_wheel
  3. Upload release: twine upload --repository-url 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


Raymond Xia -

Mahmoud Alismail -

Shangwu Yao -

Andrew Wu -

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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