Urdu · Datasets · 9 min read
Urdu Speech Datasets for ASR: What AI Teams Should Evaluate
Urdu is spoken by well over 200 million people, yet it remains thin in web data. Here is what to check before you train or test an Urdu speech model.
Human-verified speech data and independent voice AI evaluation for Saraiki, Pakistani Punjabi and Urdu, recorded with consent in real homes, markets and fields.
of web addresses in Common Crawl's July 2026 collection were Urdu, for a language spoken by well over 200 million people.
Source: World Bank figures via K. Zafar, Oct 2026national AI programme in Pakistan, including a sovereign multilingual model that will need local-language speech and text.
Source: K. Zafar, Oct 2026projected AI training dataset market by 2034, up from $3.2B in 2024 (20.5% CAGR).
Source: Global Market InsightsEvery recording is tied to a district, a dialect and a signed consent. Select a district to see what we collect there.
"Assaan ghar wanjna ae": "We have to go home" in Saraiki. Tens of millions speak it, yet written Saraiki barely exists online, so models trained on Urdu text turn it into Urdu.
Start with one pilot. Most teams add collection and monthly regression testing once they see the first report.
We test your ASR, TTS or voice agent on speech it has never heard and show exactly where it breaks.
Scripted or natural conversation recorded to your spec, with speaker demographics and recording conditions logged.
Native-speaker transcription, translation and LLM response rating for languages your vendors can't staff.
We report errors by cause, so your team knows what to fix first instead of staring at one average score.
A fixed-scope pilot of 100 consented utterances. You see our quality before any larger commitment.
Choose languages, recording conditions and the model or API to test.
Consented speakers recorded; every reference checked by two reviewers.
Error classes, examples and priorities, delivered with all raw files.
The same private test set on each new model version.
Every speaker hears what the recording is for in Saraiki, Punjabi or Urdu before signing.
Speakers are paid for their time. No recording without payment.
Each dataset ships with a licence file, speaker metadata and provenance record.
Evaluation audio is never published, so your scores stay meaningful.
Files shared through restricted links with access logs; NDA available.
Speakers can ask for future use of their voice to stop; we track it per clip.
Practical notes for speech and LLM teams working on South Asian languages.
We launch with Saraiki, Pakistani Punjabi and Urdu, including Urdu–English code-switching. Sindhi and Pashto come next, then Balochi. We mark a language live only when we have verified speakers and reviewers for it.
Pakistani Punjabi and Saraiki differ in vocabulary, script, accent and everyday code-switching. We record in Pakistani districts with local speakers, so the audio matches what your users in Pakistan and its diaspora actually say.
100 consented utterances, verified reference transcripts, your model's outputs, an error report grouped by cause, speaker metadata and a licence file.
Yes. Give us test access to your API or upload outputs yourself. We never use your model outputs or evaluation results for anyone else.
For custom collection, you receive a licence suited to your use, agreed before recording starts and explained to every speaker. Evaluation test sets stay private by default.
A fixed-scope pilot across Saraiki, Pakistani Punjabi and Urdu with a full error report. You keep the findings.