Speech AI Companies · Kannada
Kannada Training Data for Speech AI Companies
Teams whose core product is speech recognition or synthesis, where dataset quality is the product roadmap and word error rate is the metric everyone watches. For Kannada specifically, the work is shaped by 5 dialect varieties and by how much English enters the speech.
- Buyer profile
- Speech AI Companies
- Language
- Kannada (kn-IN)
- Typical ask
- 500-2
Your problem
- WER on Indian languages is dominated by dialect and code-mixing failures that generic corpora do not cover
- Public Indic corpora are read speech and do not transfer to spontaneous production audio
- Benchmark sets leak speakers into training splits, inflating reported accuracy
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
- Are train/dev/test splits speaker-disjoint by construction?
- Is transcription verbatim, with disfluencies preserved?
- Is per-token language ID available for code-mixed speech?
- Is inter-annotator agreement measured and reported?
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
- Speaker-disjoint splits guaranteed contractually
- Right to publish benchmark results
- Re-record remedy for QA failures
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. Speaker-disjoint splits guaranteed contractually is addressed in the master agreement.
Request a Kannada quote
Send the spec. You get scope, timeline and price.