Metadata-Version: 2.1
Name: audlib
Version: 0.0.3.2
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
Description: # audlib
        
        [![PyPI version](https://badge.fury.io/py/audlib.svg)](https://badge.fury.io/py/audlib)
        [![Build Status](https://travis-ci.com/raymondxyy/pyaudlib.svg?token=xNuzdfgseSXz1yHDnh9L&branch=master)](https://travis-ci.org/raymondxyy/pyaudlib)
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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
          - I/O utilities for interfacing with [CMUSPHINX][sphinx]
        
        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][pytorch]'s convention.
        
        ## Breaking Changes
        
        - 0.0.3
          - `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
        
        ## Authors
        
        Raymond Xia - raymondxia@cmu.edu
        
        Mahmoud Alismail - mahmoudi@andrew.cmu.edu
        
        Shangwu Yao - shangwuyao@gmail.com
        
        Andrew Wu - anwu.andrew@hotmail.com
        
        Feel free to send us any issue you find and question you have.
        
        ## Contributing
        
        Please contact one of the authors.
        
        ## License
        
        Distributed under the MIT license. See ``LICENSE`` for more information.
        
        [pytorch]: https://pytorch.org/
        [sphinx]: https://cmusphinx.github.io/
        
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
Provides-Extra: tests
Provides-Extra: nn
Provides-Extra: display
