Speech AI Companies · Urdu
Urdu 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 Urdu specifically, the work is shaped by 5 dialect varieties and by how much English enters the speech.
- Buyer profile
- Speech AI Companies
- Language
- Urdu (ur-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 Urdu requires
- Shares most phonology with Hindi but adds Perso-Arabic phonemes (/q/, /x/, /ɣ/, /z/, /f/) that many speakers merge
- Dialects: 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.
- Indian Urdu specifically, and Dakhini in particular, are absent from public data dominated by Pakistani Urdu broadcast speech.
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
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 |
Contract points
- Speaker-disjoint splits guaranteed contractually
- Right to publish benchmark results
- Re-record remedy for QA failures
Example requirement
"We need 1,000 hours of Urdu from 1,500 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 Urdu capacity available now?
Fix the script decision before fielding; retro-transcribing a Nastaliq dataset into Devanagari after delivery costs as much as the original transcription pass. 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 Urdu 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 Urdu quote
Send the spec. You get scope, timeline and price.