Use a previously trained Tensorflow micmon sound model to make predictions on sound segments from a microphone

micmon_predict_example.py

import os

from micmon.audio import AudioDevice
from micmon.model import Model

model_dir = os.path.expanduser('~/models/sound-detect')
model = Model.load(model_dir)
audio_system = 'alsa'        # Supported: alsa and pulse
audio_device = 'plughw:2,0'  # Get list of recognized input devices with arecord -l

with AudioDevice(audio_system, device=audio_device) as source:
    for sample in source:
        source.pause()  # Pause recording while we process the frame
        prediction = model.predict(sample)
        print(prediction)
        source.resume() # Resume recording

hello, I have a question, how can we inference model with audio file instead of microphone?

@dovanhuong If you look at the micmon.audio package you'll find an AudioFile object that exposes a similar interface as AudioDevice. So just replacing AudioDevice with AudioFile (and specifying a source file instead of a source device) should suffice.

@blacklight thank you for your advice, I'll take a look on it!