Metadata-Version: 2.1
Name: webrtcvad
Version: 2.0.10
Summary: Python interface to the Google WebRTC Voice Activity Detector (VAD)
Home-page: https://github.com/wiseman/py-webrtcvad
Author: John Wiseman
Author-email: jjwiseman@gmail.com
License: MIT
Description: .. image:: https://travis-ci.org/wiseman/py-webrtcvad.svg?branch=master
            :target: https://travis-ci.org/wiseman/py-webrtcvad
        
        py-webrtcvad
        ============
        
        This is a python interface to the WebRTC Voice Activity Detector
        (VAD).  It is compatible with Python 2 and Python 3.
        
        A `VAD <https://en.wikipedia.org/wiki/Voice_activity_detection>`_
        classifies a piece of audio data as being voiced or unvoiced. It can
        be useful for telephony and speech recognition.
        
        The VAD that Google developed for the `WebRTC <https://webrtc.org/>`_
        project is reportedly one of the best available, being fast, modern
        and free.
        
        How to use it
        -------------
        
        0. Install the webrtcvad module::
        
            pip install webrtcvad
        
        1. Create a ``Vad`` object::
        
            import webrtcvad
            vad = webrtcvad.Vad()
        
        2. Optionally, set its aggressiveness mode, which is an integer
           between 0 and 3. 0 is the least aggressive about filtering out
           non-speech, 3 is the most aggressive. (You can also set the mode
           when you create the VAD, e.g. ``vad = webrtcvad.Vad(3)``)::
        
            vad.set_mode(1)
        
        3. Give it a short segment ("frame") of audio. The WebRTC VAD only
           accepts 16-bit mono PCM audio, sampled at 8000, 16000, or 32000 Hz.
           A frame must be either 10, 20, or 30 ms in duration::
        
            # Run the VAD on 10 ms of silence. The result should be False.
            sample_rate = 16000
            frame_duration = 10  # ms
            frame = b'\x00\x00' * (sample_rate * frame_duration / 1000)
            print 'Contains speech: %s' % (vad.is_speech(frame, sample_rate)
        
        
        See `example.py
        <https://github.com/wiseman/py-webrtcvad/blob/master/example.py>`_ for
        a more detailed example that will process a .wav file, find the voiced
        segments, and write each one as a separate .wav.
        
        
        How to run unit tests
        ---------------------
        
        To run unit tests::
        
            pip install -e ".[dev]"
            python setup.py test
        
Keywords: speechrecognition asr voiceactivitydetection vad webrtc
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Provides-Extra: dev