Speech AI Companies · Hinglish
Hinglish Training Data for Speech AI Companies
Teams whose core product is speech recognition or synthesis, where dataset quality is the product roadmap and word error rate is the metric everyone watches. For Hinglish specifically, the work is shaped by 4 dialect varieties and by how much English enters the speech.
- Buyer profile
- Speech AI Companies
- Language
- Hinglish (hi-Latn-IN)
- Typical ask
- 500-2
Your problem
- WER on Indian languages is dominated by dialect and code-mixing failures that generic corpora do not cover
- Public Indic corpora are read speech and do not transfer to spontaneous production audio
- Benchmark sets leak speakers into training splits, inflating reported accuracy
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
- Are train/dev/test splits speaker-disjoint by construction?
- Is transcription verbatim, with disfluencies preserved?
- Is per-token language ID available for code-mixed speech?
- Is inter-annotator agreement measured and reported?
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
- Speaker-disjoint splits guaranteed contractually
- Right to publish benchmark results
- Re-record remedy for QA failures
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. Speaker-disjoint splits guaranteed contractually is addressed in the master agreement.
Request a Hinglish quote
Send the spec. You get scope, timeline and price.