Model without JSON

JSON is recommended but not required. If you only have a .tflite model, use a builder and provide the missing settings.

Microphone listener

use micro_wakeword::Listener;

# fn run() -> micro_wakeword::Result<()> {
let mut listener = Listener::builder("hey_computer.tflite")
    .wake_word("hey computer")
    .probability_cutoff(0.5)
    .sliding_window_size(3)
    .build()?;
# Ok(()) }

Low-level detector

use micro_wakeword::Detector;

# fn run() -> micro_wakeword::Result<()> {
let mut detector = Detector::builder("hey_computer.tflite")
    .wake_word("hey computer")
    .probability_cutoff(0.5)
    .sliding_window_size(3)
    .build()?;
# Ok(()) }

Does the crate guess values?

No. A TFLite file describes tensors and operations, but standard microWakeWord cutoffs and smoothing choices are distribution metadata, not reliably recoverable settings. The builder requires the wake-word name, cutoff, and sliding-window size; it does not invent them. Only the fixed 10 ms feature step and automatic runtime selection have defaults.

Prefer values from the model author or its original JSON. If neither exists, test candidate values against:

many recordings containing the wake phrase;
similar phrases that should not trigger;
ordinary conversations;
silence, music, television, and expected background noise;
the actual microphones and rooms where the app will run.