LLM human data · Speech Analytics
Human Data for LLM Projects for Speech Analytics
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 speech analytics, the specification is driven by one thing: intent accuracy.
- Service
- LLM human data
- Use case
- Speech Analytics
- Primary metric
- Intent accuracy
Required data profile
- Domain-realistic conversation audio
- Intent, outcome and compliance labels
- Speaker-separated channels
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
- Intent accuracy
- Compliance-event recall
- Summary factuality
Failure modes to design out
- Labels defined without listening to real calls first
- Ignoring dialect coverage in the target market
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 speech analytics?
It covers domain-realistic conversation audio. Most speech analytics 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 speech analytics
Send the metric you need to move.