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
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
License-File: LICENSE

.. 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


