Transcription · Wake Word Detection
Transcription Services for Wake Word Detection
Verbatim and clean-read transcription of Indian-language audio by native speakers of the target variety, delivered against a written style guide with measured agreement. Applied to wake word detection, the specification is driven by one thing: false accepts per hour.
- Service
- Transcription
- 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 |
|---|---|
| Modes | Verbatim, clean verbatim, or clean-read |
| Timestamps | Utterance or word level |
| Script | Native script, romanised, or dual-script delivery |
| Tags | Speaker, noise, overlap, unintelligible, code-switch |
| Accuracy target | 99% on clean studio audio; agreed per-project on field audio |
Process
- Style guide authoring and client sign-off
- Transcriber calibration and agreement measurement
- First pass transcription
- Independent second-pass review
- Automated rule checks and delivery
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
The style guide is the deliverable that determines whether your data is usable. It is written first and shipped with the data.
Deliverables
- Transcripts in your schema
- Style guide
- QA and agreement report
Frequently asked
Is transcription 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 transcription for wake word detection
Send the metric you need to move.