A TensorFlow based wake word detection training framework using synthetic sample generation suitable for certain microcontrollers.
Project description
Python microWakeWord
Python library for microWakeWord.
Uses a pre-compiled Tensorflow Lite library.
Install
pip3 install pymicro-wakeword
Usage
from pymicro_wakeword import MicroWakeWord, MicroWakeWordFeatures, Model
mww = MicroWakeWord.from_builtin(Model.OKAY_NABU)
mww_features = MicroWakeWordFeatures()
# Audio must be 16-bit mono at 16Khz
while audio := get_10ms_of_audio():
assert len(audio) == 160 * 2 # 160 samples
for features in mww_features.process_streaming(audio):
if mww.process_streaming(features):
print("Detected!")
Command-Line
WAVE files
python3 -m pymicro_wakeword --model 'okay_nabu' /path/to/*.wav
Live
arecord -r 16000 -c 1 -f S16_LE -t raw | \
python3 -m pymicro_wakeword --model 'okay_nabu'
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