LLM Companies · Hinglish
Hinglish Training Data for LLM Companies
Foundation and applied LLM teams that need Indian-language human data with provable provenance, covering languages their web crawl barely touched. For Hinglish specifically, the work is shaped by 4 dialect varieties and by how much English enters the speech.
- Buyer profile
- LLM Companies
- Language
- Hinglish (hi-Latn-IN)
- Typical ask
- Instruction-response pairs
Your problem
- Web-scraped Indian-language text is thin, noisy and heavily transliterated
- Code-mixed Hinglish is nearly absent from any structured training source
- Provenance and consent for human-generated data must survive external audit
What Hinglish requires
- Intra-sentential switching means English words carry Indian phonology, so English acoustic models mis-transcribe them
- Dialects: Delhi corporate Hinglish, Mumbai Bambaiya, Call-centre register, Youth/social media register
- Hinglish is the code-mixing case itself. Typical urban customer-support speech is 30-60% English tokens embedded in Hindi grammar, with switching several times per utterance.
- Almost no public corpus contains genuine intra-sentential Hindi-English switching with per-token language tags. This is the highest-value gap for anyone building Indian conversational AI.
How you will evaluate the delivery
- Is every item traceable to a screened, consenting contributor?
- Can contributors be screened by domain expertise, not just language?
- Is there an adjudication process for disagreement on subjective tasks?
Recommended cohort
Recruit by switching behaviour, not by language proficiency. Screening recordings are used to confirm speakers switch naturally rather than performing one language.
| Dimension | Typical split | Why it matters for Hinglish |
|---|---|---|
| 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 Hinglish forms that younger urban speakers have lost |
| Region | Delhi NCR / Mumbai / Bengaluru and others | Dialect spread across 4 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 |
Contract points
- Auditable provenance records
- Contributor consent for model training and distribution
- No third-party or scraped content in deliverables
Example requirement
"We need 2,000 hours of Hinglish from 3,000 speakers, 50/50 male-female, ages 18-45, studio quality, scripted plus spontaneous, delivered in WAV with transcripts."
That sentence is enough to produce a quote and a timeline. Anything missing, we will ask about once.
Frequently asked
Do you have Hinglish capacity available now?
Recruit by switching behaviour, not by language proficiency. Screening recordings are used to confirm speakers switch naturally rather than performing one language. Fielding usually starts one to two weeks after the specification is signed.
Can you work white-label?
Yes, including QA reporting written so it can be passed to your end client unchanged.
What licensing applies to Hinglish data?
Perpetual and transferable, with participant consent covering model training and downstream distribution. Auditable provenance records is addressed in the master agreement.
Request a Hinglish quote
Send the spec. You get scope, timeline and price.