Metadata-Version: 1.2
Name: opensmile
Version: 1.0.1
Summary: Python wrapper for common openSMILE feature sets
Home-page: https://github.com/audeering/opensmile-python/
Author: Johannes Wagner, Christoph Hausner, Hagen Wierstorf
Author-email: jwagner@audeering.com, chausner@audeering.com, hwierstorf@audeering.com
License: audEERING
Project-URL: Documentation, https://audeering.github.io/opensmile-python/
Description: ================
        openSMILE Python
        ================
        
        |tests| |coverage| |docs| |python-versions| |license| 
        
        Python interface for extracting openSMILE_ features.
        
        .. code-block::
        
            $ pip install opensmile
        
        .. note:: Only 64-bit Python is supported.
        
        Feature sets
        ------------
        
        Currently, three standard sets are supported.
        `ComParE 2016`_ is the largest with more than 6k features.
        The smaller sets GeMAPS_ and  eGeMAPS_
        come in two variants ``v01a`` and ``v01b``.
        We suggest to use the newer version
        unless backward compatibility with
        the original papers is desired.
        
        Each feature set can be extracted on three levels:
        
        * Low-level descriptors (LDD)
        * LLDs with deltas
        * Functionals
        
        The following table lists the number of features
        for each set and level.
        
        ============  ==============
        Name          #features
        ============  ==============
        ComParE_2016  65 / 65 / 6373
        GeMAPSv01a    5 / 13 / 62
        GeMAPSv01b    62 / 13 / 62
        eGeMAPSv01a   10 / 13 / 88
        eGeMAPSv01b   10 / 13 / 88
        ============  ==============
        
        Code example
        ------------
        
        Code example,
        that extracts `ComParE 2016`_  functionals from an audio file:
        
        .. code-block:: python
        
            import opensmile
        
            smile = opensmile.Smile(
                feature_set=opensmile.FeatureSet.ComParE_2016,
                feature_level=opensmile.FeatureLevel.Functionals,
            )
            y = smile.process_file('audio.wav')
        
        License
        -------
        
        openSMILE follows a dual-licensing model. Since the main goal of the project
        is a widespread use of the software to facilitate research in the field of
        machine learning from audio-visual signals, the source code and binaries are
        freely available for private, research, and educational use under an open-source license
        (see LICENSE).
        It is not allowed to use the open-source version of openSMILE for any sort of commercial product.
        Fundamental research in companies, for example, is permitted, but if a product is the result of
        the research, we require you to buy a commercial development license.
        Contact us at info@audeering.com (or visit us at https://www.audeering.com) for more information.
        
        Original authors: Florian Eyben, Felix Weninger, Martin Wöllmer, Björn Schuller
        
        Copyright © 2008-2013, Institute for Human-Machine Communication, Technische Universität München, Germany
        
        Copyright © 2013-2015, audEERING UG (haftungsbeschränkt)
        
        Copyright © 2016-2020, audEERING GmbH
        
        Citing
        ------
        
        Please cite openSMILE in your publications by citing the following paper:
        
            Florian Eyben, Martin Wöllmer, Björn Schuller: "openSMILE - The Munich Versatile and Fast Open-Source Audio Feature Extractor", Proc. ACM Multimedia (MM), ACM, Florence, Italy, ISBN 978-1-60558-933-6, pp. 1459-1462, 25.-29.10.2010.
        
        
        .. _openSMILE: https://github.com/audeering/opensmile
        .. _ComParE 2016: http://www.tangsoo.de/documents/Publications/Schuller16-TI2.pdf
        .. _GeMAPS: https://sail.usc.edu/publications/files/eyben-preprinttaffc-2015.pdf
        .. _eGeMAPS: https://sail.usc.edu/publications/files/eyben-preprinttaffc-2015.pdf
        
        .. badges images and links:
        .. |tests| image:: https://github.com/audeering/opensmile-python/workflows/Test/badge.svg
            :target: https://github.com/audeering/opensmile-python/actions?query=workflow%3ATest
            :alt: Test status
        .. |coverage| image:: https://codecov.io/gh/audeering/opensmile-python/branch/master/graph/badge.svg?token=PUA9P2UJW1
            :target: https://codecov.io/gh/audeering/opensmile-python
            :alt: code coverage
        .. |docs| image:: https://img.shields.io/pypi/v/opensmile?label=docs
            :target: https://audeering.github.io/opensmile-python/
            :alt: opensmile's documentation
        .. |license| image:: https://img.shields.io/badge/license-audEERING-red.svg
            :target: https://github.com/audeering/opensmile-python/blob/master/LICENSE
            :alt: opensmile's audEERING license
        .. |python-versions| image:: https://img.shields.io/pypi/pyversions/opensmile.svg
            :target: https://pypi.org/project/opensmile/
            :alt: opensmile's supported Python versions
        
Keywords: audio,tools,feature,opensmile,audeering
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
