TTS datasets · اردو
Urdu TTS Training Data
Single-speaker and multi-speaker text-to-speech corpora with phonetically balanced scripts, consistent prosody, and studio-grade capture suitable for neural TTS. This page covers how that works specifically for Urdu, where shares most phonology with hindi but adds perso-arabic phonemes (/q/, /x/, /ɣ/, /z/, /f/) that many speakers merge.
- Language
- Urdu (ur-IN)
- Dialects covered
- 5
- Typical programme
- 250-1,000 hours
- Cities
- Hyderabad, Lucknow, Delhi
What changes when the language is Urdu
The service specification stays constant across languages; the linguistics do not. For Urdu, three things drive the design of a tts datasets programme.
- Shares most phonology with Hindi but adds Perso-Arabic phonemes (/q/, /x/, /ɣ/, /z/, /f/) that many speakers merge
- Dialect spread: 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.
Technical specification
| Parameter | Standard |
|---|---|
| Sample rate | 48 kHz, 24-bit |
| Speaker consistency | Same booth, mic, distance and time-of-day banding across sessions |
| Script | Phonetically balanced, diphone-covering, domain-extended |
| Prosody | Neutral base set plus optional expressive styles |
| Alignment | Text-audio alignment verified per utterance |
| Silence | Leading/trailing silence trimmed to a fixed window |
Urdu cohort design
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 |
Process
- Script generation with phoneme and diphone coverage analysis
- Voice casting with client shortlisting from audition samples
- Multi-session recording with drift monitoring between sessions
- Alignment verification and mispronunciation review by a linguist
- Delivery with a coverage report
Urdu-specific quality rules
- Right-to-left Nastaliq tooling errors and diacritic loss
- Merged phonemes transcribed by sound rather than by etymology, or vice versa, inconsistently
- Dakhini forms replaced with standard Urdu
Session drift is the main TTS killer. Every session is compared acoustically against the reference session and re-recorded if it drifts.
Deliverables
- Studio WAV per utterance
- Verified transcripts and pronunciation notes
- Phoneme coverage report
- Voice talent licence and consent documentation
Worked example
A representative Urdu tts datasets engagement: 250 hours from 500 speakers, 50/50 gender, ages 18-45, spread across Hyderabad, Lucknow, Delhi, recorded to the specification above and delivered in WAV with a per-utterance manifest.
Timeline: 4-8 weeks for a 20-40 hour single-speaker voice build including casting.
Where this data is missing today
Indian Urdu specifically, and Dakhini in particular, are absent from public data dominated by Pakistani Urdu broadcast speech.
Frequently asked
How much does Urdu tts datasets cost?
Priced per delivered hour or unit against a written spec. The cost drivers for Urdu are dialect spread, demographic narrowness and recording condition, in that order.
Which Urdu dialects are included?
By default Dakhini (Hyderabad), Lucknawi, Dehlvi, Bihari Urdu and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.
Can you deliver Urdu data in our format?
Yes. Studio WAV per utterance is the default, but naming, schema and directory structure follow your pipeline.
How long does a Urdu programme take?
4-8 weeks for a 20-40 hour single-speaker voice build including casting.
Request a Urdu tts datasets quote
Hours, speakers, dialects, deadline. Send what you have.