.. 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
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