Audio annotation · Code-Switching ASR
Audio Annotation for Code-Switching ASR
Labelling of existing audio: speaker diarisation, emotion, intent, events, language identification and segment-level quality tagging, against your label schema. Applied to code-switching asr, the specification is driven by one thing: switch-point accuracy.
- Service
- Audio annotation
- Use case
- Code-Switching ASR
- Primary metric
- Switch-point accuracy
Required data profile
- Genuinely code-mixed spontaneous speech
- Per-token language ID labels
- A fixed rule for script of English tokens
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
- Switch-point accuracy
- Mixed-utterance WER
- Language ID token accuracy
Failure modes to design out
- Concatenating monolingual data and calling it code-mixed
- Leaving script conventions to individual annotators
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 code-switching asr?
It covers genuinely code-mixed spontaneous speech. Most code-switching asr 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 code-switching asr
Send the metric you need to move.