LLM human data · Voice Biometrics
Human Data for LLM Projects for Voice Biometrics
Human-generated text and speech for LLM training and evaluation in Indian languages: prompts, preference rankings, instruction-response pairs, red-teaming and cultural-fit review. Applied to voice biometrics, the specification is driven by one thing: equal error rate.
- Service
- LLM human data
- Use case
- Voice Biometrics
- Primary metric
- Equal error rate
Required data profile
- Many sessions per speaker across days and channels
- Same-speaker channel variation
- Optional spoof and replay sets
Technical specification
| Parameter | Standard |
|---|---|
| Task types | Prompt writing, response ranking, instruction-response pairs, adversarial testing |
| Languages | Any language in the network, including code-mixed Hinglish |
| Contributors | Screened by domain, education band and language proficiency |
| Agreement | Overlapping assignments with adjudication |
| Provenance | Per-item contributor and time records |
Process
- Task specification and rubric design
- Contributor screening against the rubric
- Calibration round with feedback
- Production with overlap and gold items
- Adjudication and delivery
Metrics this feeds
- Equal error rate
- Cross-channel EER
- Spoof detection rate
Failure modes to design out
- One session per speaker, which makes intra-speaker variability unmodellable
- No channel variation
Every item is traceable to a screened contributor, which matters when a model vendor audits your data provenance.
Deliverables
- Task data in your schema
- Rubric and calibration results
- Contributor metadata (anonymised)
- Agreement statistics
Frequently asked
Is llm human data the right service for voice biometrics?
It covers many sessions per speaker across days and channels. Most voice biometrics 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 llm human data for voice biometrics
Send the metric you need to move.