I’m confused about how preprocessor models work. My initial understanding was that a preprocessor was creating spectrograms of what it “hears” with little regard for the specific sound.
But in this file:
tensorflow/lite/micro/examples/micro_speech/audio_preprocessor.py
I read things like this:
_FILE_TO_TEST = flags.DEFINE_enum('file_to_test', 'no', ['no', 'yes'],
'File to test')
To me, that implies the preprocessor is sensitive to specific keywords.
Can someone clarify?
Thanks,
-T