Troubleshooting

Detections fire constantly

• Confirm the model and JSON belong together.
• Increase probability_cutoff or sliding_window_size carefully.
• Use the listener cooldown for repeated matches of the same utterance.
• Evaluate with negative recordings, not only live intuition.

Wake words are missed

• Run an optimized build with cargo run --release.
• Confirm the selected microphone and its input level.
• Start from model-author settings.
• Lower the cutoff or window only after measuring false activations.

AudioStreamEnded

The device or capture channel ended. Drop and recreate the listener. If no device was selected explicitly, the new listener asks the OS for its current default. See Disconnect & reconnect.

Dropped audio blocks keep increasing

The process is not consuming audio in real time. Use release mode, hand expensive work to another thread, and inspect system CPU pressure. The listener automatically drains stale blocks and resets after a gap.

“Expected exactly 160 samples”

Detector::process_audio accepts one 10 ms block per call. Re-buffer your decoded stream into exactly 160-sample chunks. Also verify 16 kHz, mono, signed i16 PCM.

JSON loads but the model does not

The model path is relative to the JSON file. Check that the .tflite file exists there and that its tensor contract is compatible.

TensorFlow Lite cannot be loaded

Windows x86-64 uses the bundled runtime unless an environment variable overrides it. On other platforms, supply a compatible shared library with Runtime::from_path(...) or configure the system loader.

Device name is ambiguous

Call available_input_devices(), then use the full name or the index displayed in the current run.