Microphone VAD Streaming
========================
Stream from microphone to DeepSpeech, using VAD (voice activity detection). A fairly simple example demonstrating the DeepSpeech streaming API in Python. Also useful for quick, real-time testing of models and decoding parameters.
Installation
------------
.. code-block:: bash
pip install -r requirements.txt
Uses portaudio for microphone access, so on Linux, you may need to install its header files to compile the ``pyaudio`` package:
.. code-block:: bash
sudo apt install portaudio19-dev
Installation on MacOS may fail due to portaudio, use brew to install it:
.. code-block:: bash
brew install portaudio
Usage
-----
.. code-block::
usage: mic_vad_streaming.py [-h] [-v VAD_AGGRESSIVENESS] [--nospinner]
[-w SAVEWAV] [-f FILE] -m MODEL [-s SCORER]
[-d DEVICE] [-r RATE]
Stream from microphone to DeepSpeech using VAD
optional arguments:
-h, --help show this help message and exit
-v VAD_AGGRESSIVENESS, --vad_aggressiveness VAD_AGGRESSIVENESS
Set aggressiveness of VAD: an integer between 0 and 3,
0 being the least aggressive about filtering out non-
speech, 3 the most aggressive. Default: 3
--nospinner Disable spinner
-w SAVEWAV, --savewav SAVEWAV
Save .wav files of utterences to given directory
-f FILE, --file FILE Read from .wav file instead of microphone
-m MODEL, --model MODEL
Path to the model (protocol buffer binary file, or
entire directory containing all standard-named files
for model)
-s SCORER, --scorer SCORER
Path to the external scorer file. Default:
kenlm.scorer
-d DEVICE, --device DEVICE
Device input index (Int) as listed by
pyaudio.PyAudio.get_device_info_by_index(). If not
provided, falls back to PyAudio.get_default_device().
-r RATE, --rate RATE Input device sample rate. Default: 16000. Your device
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