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        "author": "John Wiseman",
        "author_email": "jjwiseman@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Human Machine Interfaces",
            "Topic :: Scientific/Engineering :: Information Analysis"
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        "description": ".. image:: https://travis-ci.org/wiseman/py-webrtcvad.svg?branch=master\n    :target: https://travis-ci.org/wiseman/py-webrtcvad\n\npy-webrtcvad\n============\n\nThis is a python interface to the WebRTC Voice Activity Detector\n(VAD).  It is compatible with Python 2 and Python 3.\n\nA `VAD <https://en.wikipedia.org/wiki/Voice_activity_detection>`_\nclassifies a piece of audio data as being voiced or unvoiced. It can\nbe useful for telephony and speech recognition.\n\nThe VAD that Google developed for the `WebRTC <https://webrtc.org/>`_\nproject is reportedly one of the best available, being fast, modern\nand free.\n\nHow to use it\n-------------\n\n0. Install the webrtcvad module::\n\n    pip install webrtcvad\n\n1. Create a ``Vad`` object::\n\n    import webrtcvad\n    vad = webrtcvad.Vad()\n\n2. Optionally, set its aggressiveness mode, which is an integer\n   between 0 and 3. 0 is the least aggressive about filtering out\n   non-speech, 3 is the most aggressive. (You can also set the mode\n   when you create the VAD, e.g. ``vad = webrtcvad.Vad(3)``)::\n\n    vad.set_mode(1)\n\n3. Give it a short segment (\"frame\") of audio. The WebRTC VAD only\n   accepts 16-bit mono PCM audio, sampled at 8000, 16000, or 32000 Hz.\n   A frame must be either 10, 20, or 30 ms in duration::\n\n    # Run the VAD on 10 ms of silence. The result should be False.\n    sample_rate = 16000\n    frame_duration = 10  # ms\n    frame = b'\\x00\\x00' * (sample_rate * frame_duration / 1000)\n    print 'Contains speech: %s' % (vad.is_speech(frame, sample_rate)\n\n\nSee `example.py\n<https://github.com/wiseman/py-webrtcvad/blob/master/example.py>`_ for\na more detailed example that will process a .wav file, find the voiced\nsegments, and write each one as a separate .wav.\n\n\nHow to run unit tests\n---------------------\n\nTo run unit tests::\n\n    pip install -e \".[dev]\"\n    python setup.py test",
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