ovos-ww-verifier-plugin-speaker

An OVOS wake word verifier plugin. It accepts voice commands only from enrolled household members.

After a wake word engine detects an activation, this verifier extracts a speaker embedding from the captured audio. It compares the embedding against enrolled profiles. The plugin silently drops activations from unrecognized speakers.

Use case

Alice and Bob live together and use OVOS at home. They enroll their voices once. A guest's "Hey Mycroft" still triggers the wake word detector, but the speaker verifier rejects it before any intent is processed. Commands from Alice and Bob go through normally.

Privacy note

The plugin stores speaker profiles as fixed-length numeric vectors (embeddings) in a local JSON file at ~/.local/share/ovos_speaker_verifier/profiles.json. It keeps no audio after embedding extraction. You cannot reverse an embedding back into audio.

Install

pip install ovos-ww-verifier-plugin-speaker

Enroll household members

ovos-speaker-enroll Alice clip1.wav clip2.wav clip3.wav
ovos-speaker-enroll Bob morning_command.wav evening_command.wav

More clips (5 to 30 s total per person) give a more robust profile.

OVOS configuration

ovos-dinkum-listener (>= 0.6.0) loads wake-word verifiers from listener.ww_verifiers. Each key is a verifier plugin's entry-point name. Its value is that plugin's config. Add this to ~/.config/mycroft/mycroft.conf (or the OpenVoiceOS equivalent):

{
  "listener": {
    "ww_verifiers": {
      "ovos-ww-verifier-speaker": {
        "model": "wespeaker-resnet34",
        "threshold": 0.45,
        "fail_open": true
      }
    }
  }
}

Installing the plugin enables it. The listener runs every installed verifier whose config does not set "enabled": false. With no entry in ww_verifiers, the plugin still loads with its defaults. Because fail_open defaults to true, it accepts everything until you enroll at least one profile. Enroll first, then tune the threshold. To install the plugin without activating it, set "enabled": false:

{"listener": {"ww_verifiers": {"ovos-ww-verifier-speaker": {"enabled": false}}}}

What happens on a wake word

The listener runs the verifier inside wake-word detection, on the audio window that triggered the engine. The outcome decides what reaches the bus:

A rejected speaker suppresses the wake-word event itself, not only the recording, so nothing downstream sees the activation. Each decision is one INFO line in the listener log naming the matched or best-matching profile, the cosine score and the threshold applied.

This is the flow proven on a real ovos-dinkum-listener voice loop with ovos-ww-plugin-precise-onnx and its default hey_mycroft model: two synthetic voices both trigger precise-onnx on "hey mycroft, what time is it"; with voice A enrolled and fail_open false, A's clip produces both events (score 0.78 at threshold 0.45) and voice B's clip produces neither (score 0.09). To repeat it, enroll two clips of one voice, set the configuration above with "fail_open": false, start the listener, and speak the wake word as the enrolled voice and as another voice.

Configuration keys

Supported models

The model key accepts any alias from speakeronnx's registry (models are downloaded from HuggingFace on first use and cached):

Threshold tuning

The acceptance threshold is model-specific. It does not transfer between models. Cosine-similarity scales differ widely across architectures. In our tests the same enrolled-vs-guest pair scored ~0.95 / 0.89 on titanet-small, but ~0.17 / 0.14 on campplus. The default 0.45 is calibrated for the default wespeaker-resnet34. If you change model, you must re-tune threshold.

To pick a value, enroll a speaker. Then compare verify() scores for genuine and guest clips, and choose a threshold that sits between them (tests/test_ovoscope_models_e2e.py calibrates this per model automatically). For a given model, lower the threshold for noisier or distant-microphone setups. Raise it for stricter security.

Python API

from ovos_ww_verifier_plugin_speaker import SpeakerVerifier

v = SpeakerVerifier(config={"threshold": 0.45, "fail_open": False})
v.enroll("Alice", ["alice1.wav", "alice2.wav"])

# In wake word callback:
accepted = v.verify(pcm_bytes)  # True if Alice spoke

Testing

pip install -e ".[test]"
pytest tests/test_unit.py tests/test_ovoscope_e2e.py   # fast, offline

• test_unit.py: verifier policy logic (enrollment, thresholds, fail-open).
• test_ovoscope_e2e.py: drives the verifier through a real listener (ovoscope.MiniVoiceLoop) and asserts a rejected speaker suppresses recognizer_loop:record_begin on the bus. It is fast and needs no model download.
• test_e2e.py / test_ovoscope_models_e2e.py: real-model tests over every speakeronnx model. They read the committed synthetic-voice fixtures under tests/fixtures/ (two enrolment clips and one verify clip of voice A, one guest clip of voice B) and confirm only the enrolled speaker triggers the wake word. They download the models on first run and never skip. Regenerate the fixtures with python tests/generate_fixtures.py, which needs edge-tts and ffmpeg.

Dependencies

• speakeronnx (onnxruntime + numpy + huggingface_hub)
• ovos-plugin-manager

Credits

Developed by TigreGótico for OpenVoiceOS.

This project was funded through the NGI0 Commons Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 101135429.