Conversational AI Companies · Kannada
Kannada 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 Kannada specifically, the work is shaped by 5 dialect varieties and by how much English enters the speech.
- Buyer profile
- Conversational AI Companies
- Language
- Kannada (kn-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 Kannada requires
- North Karnataka speech has markedly different intonation and lexicon from Mysuru standard
- Dialects: Bangalore urban, Mysuru (standard literary), Dharwad / North Karnataka, Mangaluru coastal
- Bengaluru is a migration city: Kannada speech there is mixed with English, Hindi, Tamil and Telugu. Native-only Kannada cohorts recruited in Bengaluru are hard to fill without screening for years of residence.
- Mysuru/Bengaluru standard dominates. North Karnataka (Dharwad, Kalaburagi) and coastal Mangaluru speech are barely represented in any public corpus.
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
Screen Bengaluru participants for native fluency and years of Karnataka residence; otherwise the cohort drifts towards second-language Kannada.
| Dimension | Typical split | Why it matters for Kannada |
|---|---|---|
| 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 Kannada forms that younger urban speakers have lost |
| Region | Karnataka / parts of Maharashtra, Tamil Nadu and Andhra Pradesh 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 Kannada 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 Kannada capacity available now?
Screen Bengaluru participants for native fluency and years of Karnataka residence; otherwise the cohort drifts towards second-language Kannada. 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 Kannada data?
Perpetual and transferable, with participant consent covering model training and downstream distribution. Scenario confidentiality is addressed in the master agreement.
Request a Kannada quote
Send the spec. You get scope, timeline and price.