Audio annotation · Machine Translation
Audio Annotation for Machine Translation
Labelling of existing audio: speaker diarisation, emotion, intent, events, language identification and segment-level quality tagging, against your label schema. Applied to machine translation, the specification is driven by one thing: human adequacy and fluency scores.
- Service
- Audio annotation
- Use case
- Machine Translation
- Primary metric
- Human adequacy and fluency scores
Required data profile
- Sentence-aligned parallel corpora
- Register-matched to your product
- Enforced terminology glossary
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
- Human adequacy and fluency scores
- Terminology compliance rate
- Back-translation divergence
Failure modes to design out
- Pivoting everything through English
- Post-edited machine output passed off as human translation
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 machine translation?
It covers sentence-aligned parallel corpora. Most machine translation 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 machine translation
Send the metric you need to move.