Audio annotation · LLM Evaluation
Audio Annotation for LLM Evaluation
Labelling of existing audio: speaker diarisation, emotion, intent, events, language identification and segment-level quality tagging, against your label schema. Applied to llm evaluation, the specification is driven by one thing: rubric scores with confidence intervals.
- Service
- Audio annotation
- Use case
- LLM Evaluation
- Primary metric
- Rubric scores with confidence intervals
Required data profile
- Native-speaker rater panels per language
- Rubric-based scoring with calibration
- Overlapping assignments for agreement
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
- Rubric scores with confidence intervals
- Inter-rater agreement
- Failure-mode distribution
Failure modes to design out
- Raters who are fluent but not native in the variety
- Rubrics written in English and applied to non-English output without localisation
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 llm evaluation?
It covers native-speaker rater panels per language. Most llm evaluation 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 llm evaluation
Send the metric you need to move.