LLM human data · TTS Voice Building
Human Data for LLM Projects for TTS Voice Building
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 tts voice building, the specification is driven by one thing: mos naturalness.
- Service
- LLM human data
- Use case
- TTS Voice Building
- Primary metric
- MOS naturalness
Required data profile
- 10-40 hours from one speaker, or multi-speaker sets
- Phonetically balanced scripts
- Session-consistent acoustics
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
- MOS naturalness
- Pronunciation accuracy on loanwords and names
- Prosody stability across long utterances
Failure modes to design out
- Session drift between recording days
- Scripts that under-cover rare phonemes
- Uncleared voice-talent licensing
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 tts voice building?
It covers 10-40 hours from one speaker, or multi-speaker sets. Most tts voice building 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 tts voice building
Send the metric you need to move.