LLM human data · اردو
Urdu Human Data for LLM Projects
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. This page covers how that works specifically for Urdu, where shares most phonology with hindi but adds perso-arabic phonemes (/q/, /x/, /ɣ/, /z/, /f/) that many speakers merge.
- Language
- Urdu (ur-IN)
- Dialects covered
- 5
- Typical programme
- 250-1,000 hours
- Cities
- Hyderabad, Lucknow, Delhi
What changes when the language is Urdu
The service specification stays constant across languages; the linguistics do not. For Urdu, three things drive the design of a llm human data programme.
- Shares most phonology with Hindi but adds Perso-Arabic phonemes (/q/, /x/, /ɣ/, /z/, /f/) that many speakers merge
- Dialect spread: Dakhini (Hyderabad), Lucknawi, Dehlvi, Bihari Urdu
- Spoken Urdu and spoken Hindi are largely mutually intelligible; the distinction is mainly lexical and orthographic. Decide up front whether transcription is in Nastaliq, Devanagari, or both.
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 |
Urdu cohort design
Fix the script decision before fielding; retro-transcribing a Nastaliq dataset into Devanagari after delivery costs as much as the original transcription pass.
| Dimension | Typical split | Why it matters for Urdu |
|---|---|---|
| Gender | 50 / 50 | Pitch range differences change acoustic model behaviour; unbalanced cohorts bias recognition |
| Age | 18-25: 30%, 26-40: 40%, 41-60: 30% | Older speakers retain conservative Urdu forms that younger urban speakers have lost |
| Region | Uttar Pradesh / Telangana / Bihar and others | Dialect spread across 5 recognised varieties |
| Education | Mixed, including below-graduate | Prompt-reading fluency correlates with education and skews prosody |
| Condition | Studio / quiet room / field | Match the noise profile of your deployment |
Process
- Task specification and rubric design
- Contributor screening against the rubric
- Calibration round with feedback
- Production with overlap and gold items
- Adjudication and delivery
Urdu-specific quality rules
- Right-to-left Nastaliq tooling errors and diacritic loss
- Merged phonemes transcribed by sound rather than by etymology, or vice versa, inconsistently
- Dakhini forms replaced with standard Urdu
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
Worked example
A representative Urdu llm human data engagement: 250 hours from 500 speakers, 50/50 gender, ages 18-45, spread across Hyderabad, Lucknow, Delhi, recorded to the specification above and delivered in WAV with a per-utterance manifest.
Timeline: 2-6 weeks depending on task complexity and contributor screening depth.
Where this data is missing today
Indian Urdu specifically, and Dakhini in particular, are absent from public data dominated by Pakistani Urdu broadcast speech.
Frequently asked
How much does Urdu llm human data cost?
Priced per delivered hour or unit against a written spec. The cost drivers for Urdu are dialect spread, demographic narrowness and recording condition, in that order.
Which Urdu dialects are included?
By default Dakhini (Hyderabad), Lucknawi, Dehlvi, Bihari Urdu and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.
Can you deliver Urdu data in our format?
Yes. Task data in your schema is the default, but naming, schema and directory structure follow your pipeline.
How long does a Urdu programme take?
2-6 weeks depending on task complexity and contributor screening depth.
Request a Urdu llm human data quote
Hours, speakers, dialects, deadline. Send what you have.