Audio annotation · Wake Word Detection
Audio Annotation for Wake Word Detection
Labelling of existing audio: speaker diarisation, emotion, intent, events, language identification and segment-level quality tagging, against your label schema. Applied to wake word detection, the specification is driven by one thing: false accepts per hour.
- Service
- Audio annotation
- Use case
- Wake Word Detection
- Primary metric
- False accepts per hour
Required data profile
- Thousands of speakers, few utterances each
- Positive and hard-negative sets
- Multiple distances and noise conditions
Technical specification
| Parameter | Standard |
|---|---|
| Label types | Diarisation, emotion, intent, events, language ID, quality |
| Granularity | Segment, utterance, or frame-level boundaries |
| Schema | Yours, or authored with you before work starts |
| Agreement | Multi-annotator overlap on a defined percentage |
| Tooling | Client tooling supported; otherwise our annotation workflow |
Process
- Schema definition and edge-case documentation
- Annotator training and gold-set calibration
- Production annotation with gold items seeded in
- Adjudication of disagreements by a senior reviewer
- Delivery with per-label agreement statistics
Metrics this feeds
- False accepts per hour
- False reject rate per accent band
- Performance at 3m and 5m
Failure modes to design out
- Positives only, with no hard negatives
- Close-mic-only capture
- No accent-band tagging, so failures cannot be localised
Gold items are seeded throughout production so drift is caught during the run, not at delivery.
Deliverables
- Labelled data in your schema
- Gold set and calibration results
- Per-label agreement statistics
- Edge-case log
Frequently asked
Is audio annotation the right service for wake word detection?
It covers thousands of speakers, few utterances each. Most wake word detection programmes combine it with at least one other service; we will say so in the scope rather than selling one line item.
What languages are available?
All 14 languages in the network plus Indian English accent bands.
How is the evaluation set handled?
Collected first, from speakers disjoint from the training cohort, so improvement is measurable.
Scope audio annotation for wake word detection
Send the metric you need to move.