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Detection threshold

Production and offline tests use the same rule: score ≥ workflow threshold (default 0.5). The Wake Word node exposes one Threshold field in the editor — it applies to all selected models (alexa, hey_jarvis, etc.), not per model. Pass --threshold to offline tools to mirror the value saved on the node: 
# Match a workflow node set to 0.35 for hey_jarvis
python manage.py test_wake_word_wav clip.wav --model hey_jarvis --threshold 0.35
Model (fixture)Typical peak on committed WAVOften works at default 0.5?
alexa~1.0Yes
hey_mycroft~0.68Yes
hey_jarvis~0.41Often no — try 0.35–0.40

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Offline WAV test (edge worker)

Use a recording that contains the wake phrase (e.g. someone saying “alexa”). Copy into the worker container and run the bundled script: 
docker cp scripts/test_wake_word_wav.py cyberwave-worker-<ENV_UUID>:/tmp/
docker cp alexa-sample.wav cyberwave-worker-<ENV_UUID>:/tmp/

docker exec -it cyberwave-worker-<ENV_UUID> python3 /tmp/test_wake_word_wav.py \
  /tmp/alexa-sample.wav --wake-words alexa --threshold 0.5
Success (management command on compile host): 
  HIT @ 1.28s scores={'alexa': 0.512} (threshold=0.5)
Done: frames=... max_score=0.9998 @ ...s hits_above_threshold=1
On a live edge worker, look for: 
Wake word detected: 'alexa' scores={'alexa': 0.512} threshold=0.50, switching to AWAKE
The script:
  • Resamples any WAV rate/channels to 16 kHz mono int16
  • Scores 80 ms frames (1,280 samples)
  • Uses the same Model(wakeword_models=[...]) keys as production

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Django management command (compile host)

If openwakeword is installed on the backend container: 
docker compose -f local.yml exec django python manage.py test_wake_word_wav \
  src/app/tests/fixtures/audio/alexa_sample.wav --model alexa --threshold 0.5

docker compose -f local.yml exec django python manage.py test_wake_word_wav \
  src/app/tests/fixtures/audio/hey_mycroft_sample.wav --model hey_mycroft --threshold 0.5

docker compose -f local.yml exec django python manage.py test_wake_word_wav \
  src/app/tests/fixtures/audio/hey_jarvis_sample.wav --model hey_jarvis --threshold 0.5
Committed fixtures under cyberwave-backend/src/app/tests/fixtures/audio/ cover alexa, hey_mycroft, and hey_jarvis.
  • Pytest (test_wake_word_wav_detection.py, @pytest.mark.integration): asserts each fixture reaches an expected peak score (not that 0.5 always fires for every model).
  • If hey_jarvis at --threshold 0.5 prints No frame reached threshold, lower --threshold to match your workflow node or inspect max_score in the summary line.

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Live workflow checklist

CheckExpected
Audio Track bufferWake Word (80 ms) — codegen shows _CwAudioFifoBuffer(1280)
Worker init logwake_words=['alexa'] prediction_keys=['alexa']
Say wake phraseWake word detected: 'alexa' scores={'alexa': 0.5+}
Send Alert downstreamAlert name = detected wake word
Assistant signalingstart_assistant / stop_assistant on twin MQTT topic

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Common failures

SymptomCauseFix
No detection, scores always 0Stale worker using alexa_v0.1 prediction keysRecompile + sync
Scores rise but never cross thresholdThreshold too high for that model (common with hey_jarvis at 0.5)Lower Detection Threshold on the node; confirm with test_wake_word_wav and max_score
No logs from wake word nodeAudio Track 4 s bufferSet Wake Word (80 ms) buffer
Could not find pretrained model hey_siriRemoved model still in saved paramsRe-save node; pick a built-in word
Compile error: openwakeword not installedDjango image lacks ml-wakewordInstall on compile host or compile from CI with deps
No assistant soundsTwin not set on Wake Word node or FE not on environmentEnable signaling + select microphone twin

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Log levels

# docker-compose or worker env
CYBERWAVE_WORKER_LOG_LEVEL=INFO   # detection + periodic score heartbeat
CYBERWAVE_WORKER_LOG_LEVEL=DEBUG  # per-frame scores when best ≥ 0.15

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Regression tests (repo)

Backend (Docker): 
cd cyberwave-backend
docker compose -f local.yml exec -T django pytest \
  src/app/tests/test_wake_word_engine_emitter.py \
  src/app/tests/test_wake_word_engine_inputs_outputs.py
Frontend: 
cd cyberwave-frontend
pnpm test:run __tests__/openwakeword-models.test.ts __tests__/workflow-audio-chain.test.ts
Integration WAV test (requires openwakeword in test env): test_wake_word_wav_detection.py (marked @pytest.mark.integration).