Conversational AI Companies · Urdu
Urdu Training Data for Conversational AI Companies
Voice-bot and chat-plus-voice platforms deploying into Indian markets, where the gap between demo accuracy and live accuracy is a code-mixing problem. For Urdu specifically, the work is shaped by 5 dialect varieties and by how much English enters the speech.
- Buyer profile
- Conversational AI Companies
- Language
- Urdu (ur-IN)
- Typical ask
- 100-400 hours of scenario-driven conversational and telephony audio per language.
Your problem
- Bots trained on clean single-language data fail on real switching mid-utterance
- Barge-in, overlap and background noise are absent from scripted training data
- Intent coverage does not match the messy way Indian users actually phrase requests
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
- Does the data include overlap, interruptions and backchannels?
- Are utterances collected over the same channel conditions as production?
- Is intent labelling done against your live taxonomy?
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
- Scenario confidentiality
- Right to reuse across bot versions
- Delivery in a format that drops into an existing pipeline
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. Scenario confidentiality is addressed in the master agreement.
Request a Urdu quote
Send the spec. You get scope, timeline and price.