Wake word

Wake-word monitoring starts dictation when a local model detects its trained phrase. The recording stops on silence and delivers one complete transcript using your output preference. It does not ask an agent a question.

This keeps microphone monitoring active while the daemon runs. Wake-triggered dictation follows the same history preference as other dictation. Turning wake monitoring off does not close a microphone stream already used by the daemon; stop the daemon to stop its capture.

Setup

First make ordinary dictation work. You need a persistent daemon using microphone capture and a compatible wake-word model. Aria ships no wake-word model. Place an openWakeWord classifier in ~/models/wakeword as aria.onnx, beside melspectrogram.onnx and embedding_model.onnx.

Enable monitoring in ~/.aria/config.yaml:

wake:
  enabled: true
  backend: openwakeword
  model: ~/models/wakeword/aria.onnx
  threshold: 0.5

Restart the registered service and check monitoring:

aria service stop
aria service start
aria wake status

Status must report listening before you try the phrase. On macOS, leave an editable field focused and ensure Accessibility access is granted for insertion. On Linux, delivery uses the clipboard.

Speak the phrase trained into your classifier, then the sentence you want to dictate, and pause. The resulting text should arrive after recording stops. The model defines the phrase; changing the filename does not change what it recognizes. If you received a custom model, obtain its exact phrase from its builder.

Troubleshooting and stopping

aria wake status distinguishes listening, degraded, disabled, and stopped; only listening returns success. If it is degraded, inspect aria wake log and use aria doctor to check the model files. If it is disabled, check the configuration and restart after changing it.

The threshold must be greater than zero and at most one. A higher value requires a stronger match and can reduce accidental triggers; it may also miss intended ones. Adjust it only after checking the model and microphone.

To disable wake triggers, set wake.enabled: false and restart the service. Ordinary dictation remains available, including after wake inference fails. To stop the daemon itself, use aria service stop.

Models

Supported backends are openwakeword and livekit. wake.model names one classifier file. Its directory must also contain melspectrogram.onnx and embedding_model.onnx.

The livekit backend needs its own classifier and an explicit wake.model path. livekit-wakeword’s hey_livekit.onnx model recognizes “hey livekit”. A classifier must match its selected backend.

Foreground operation

For troubleshooting, you can run the daemon in the terminal with monitoring forced on. This is an alternative to the registered service:

aria service stop
aria wake run

Stop the foreground process with Ctrl-C before running aria service start to restore the registered service.