Conversational AI Companies · Punjabi
Punjabi 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 Punjabi specifically, the work is shaped by 5 dialect varieties and by how much English enters the speech.
- Buyer profile
- Conversational AI Companies
- Language
- Punjabi (pa-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 Punjabi requires
- Punjabi is tonal: high, low and level tones distinguish words, and tone is not marked in Gurmukhi orthography
- Dialects: Majhi (standard), Malwai, Doabi, Puadhi
- Punjabi speech mixes Hindi and English freely, with strong diaspora influence in urban registers.
- Tonal variation is essentially unmodelled in public Punjabi data, and Malwai/Doabi rural speech is scarce.
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
Cover all three historic regions (Majha, Malwa, Doaba); tone realisation differs measurably between them.
| Dimension | Typical split | Why it matters for Punjabi |
|---|---|---|
| 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 Punjabi forms that younger urban speakers have lost |
| Region | Punjab / Haryana / Delhi 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 500 hours of Punjabi from 800 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 Punjabi capacity available now?
Cover all three historic regions (Majha, Malwa, Doaba); tone realisation differs measurably between them. 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 Punjabi data?
Perpetual and transferable, with participant consent covering model training and downstream distribution. Scenario confidentiality is addressed in the master agreement.
Request a Punjabi quote
Send the spec. You get scope, timeline and price.