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https://github.com/wiseman/py-webrtcvad

Python interface to the WebRTC Voice Activity Detector
https://github.com/wiseman/py-webrtcvad

Last synced: 3 days ago
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Python interface to the WebRTC Voice Activity Detector

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.. 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 `_
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 `_
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, 32000 or 48000 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' * int(sample_rate * frame_duration / 1000)
print 'Contains speech: %s' % (vad.is_speech(frame, sample_rate)

See `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

History
-------

2.0.10

Fixed memory leak. Thank you, `bond005
`_!

2.0.9

Improved example code. Added WebRTC license.

2.0.8

Fixed Windows compilation errors. Thank you, `xiongyihui
`_!