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.
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:
sudo apt install portaudio19-dev
Installation on MacOS may fail due to portaudio, use brew to install it:
brew install portaudio
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