Voice Assistant Companies · Urdu
Urdu Training Data for Voice Assistant Companies
Device, OS and appliance makers shipping assistants into Indian homes and vehicles, where wake-word reliability and far-field accuracy decide the review scores. For Urdu specifically, the work is shaped by 5 dialect varieties and by how much English enters the speech.
- Buyer profile
- Voice Assistant Companies
- Language
- Urdu (ur-IN)
- Typical ask
- Wake-word positive and negative sets from 500-2
Your problem
- Wake-word false accepts and rejects spike on Indian phonetics
- Far-field and in-car conditions are not represented in close-mic corpora
- Indian names, places, brands and numbers are the most common entity failures
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
- Can recordings be captured at the distances and conditions the device sees?
- Are entity-heavy prompt sets available (names, addresses, PIN codes, amounts)?
- Can negative wake-word data be collected alongside positives?
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
- Device-specific recording conditions
- Exclusive use of the collected wake-word data
- Staged delivery per firmware milestone
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. Device-specific recording conditions is addressed in the master agreement.
Request a Urdu quote
Send the spec. You get scope, timeline and price.