ASR datasets · اردو
Urdu ASR Training Data
Transcribed speech corpora built to train and evaluate automatic speech recognition, with verbatim transcription, timestamps and per-token language tagging where code-mixing occurs. 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 asr 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 |
|---|---|
| Audio | 16 kHz or 48 kHz PCM WAV |
| Transcription | Verbatim, including disfluencies, false starts and fillers |
| Timestamps | Utterance level by default; word level on request |
| Tagging | Noise, overlap, unintelligible, foreign-language and code-switch tags |
| Normalisation | Raw and normalised text columns delivered separately |
| Split | Train/dev/test splits with no speaker leakage across splits |
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
- Style guide authored per language, covering numerals, loanwords, script and disfluency rules
- Transcriber calibration round with inter-annotator agreement measurement
- First-pass transcription
- Second-pass native review
- Automated consistency checks against the style guide
- Split generation with speaker-disjoint partitions
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
Agreement is measured, not assumed. We report word-level agreement on a held-out sample so you can judge label quality before training on it.
Deliverables
- Audio plus aligned transcripts (JSON/TSV, or your schema)
- Style guide as delivered documentation
- Inter-annotator agreement report
- Speaker-disjoint train/dev/test splits
Worked example
A representative Urdu asr 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: Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
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 asr 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. Audio plus aligned transcripts (JSON/TSV, or your schema) is the default, but naming, schema and directory structure follow your pipeline.
How long does a Urdu programme take?
Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
Request a Urdu asr datasets quote
Hours, speakers, dialects, deadline. Send what you have.