ಕನ್ನಡ · Kannada · kn-IN
Kannada AI Training Data Collection
We collect Kannada speech and language data for AI training across Karnataka, parts of Maharashtra, Tamil Nadu and Andhra Pradesh and beyond, covering 5 dialect varieties rather than a single prestige standard.
- Speakers
- 59M
- Script
- Kannada
- Studio cities
- 5
- Typical programme
- 250-1,000 hours
Why Kannada breaks generic speech models
Kannada is not a variant of a language your model already handles. The specific properties below are the ones that show up as errors in production.
- North Karnataka speech has markedly different intonation and lexicon from Mysuru standard
- Retroflex ಳ and the archaic ಱ appear in older speakers and place names
- Vowel harmony effects in colloquial speech that literary prompts never surface
Dialects we cover
Kannada has 5 varieties that matter for data collection. Collecting only the standard variety produces a model that works in the capital and fails everywhere else.
- Bangalore urban
- Mysuru (standard literary)
- Dharwad / North Karnataka
- Mangaluru coastal
- Kalyana Karnataka
Code-mixing reality
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.
Specify your expected English-token ratio in the brief. It is cheaper to collect the right mix than to filter the wrong one afterwards.
What is missing from public data
Mysuru/Bengaluru standard dominates. North Karnataka (Dharwad, Kalaburagi) and coastal Mangaluru speech are barely represented in any public corpus.
This is the practical reason to commission collection rather than assemble open corpora: the gap in the public data is exactly the part your users occupy.
Transcription rules that decide whether the data is usable
These are the Kannada-specific decisions that go into the style guide before any transcriber starts work.
- Northern lexical items replaced with standard equivalents
- Inconsistent transliteration of English technical terms
- Sandhi in connected speech transcribed as separate words by some annotators and joined by others
Recording types available
- Dialect-tagged spontaneous conversation across five zones
- Read prompts balanced for retroflex and geminate consonants
- Ride-hailing, delivery and fintech domain command sets
Recommended cohort structure
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 |
Where we record
Kannada sessions run in Bengaluru, Mysuru, Hubballi-Dharwad, Mangaluru, Kalaburagi. Multi-city fielding is the default because single-city cohorts carry an audible accent signature.
The numbers we hold ourselves to
- 100% of delivered files pass automated technical QA for SNR, clipping, duration and silence
- 5-25% of files pass a second native-speaker content review, stratified by city, dialect and transcriber, and escalating to 100% on any batch that fails the agreed threshold
- Accepted yield runs 85-90% for scripted speech, 60-70% for spontaneous, 55-65% for conversational and 50-60% for telephony
- Default cohort quotas: 50/50 gender, with age bands at 30% (18-25), 40% (26-40) and 30% (41-60)
- 48 kHz / 24-bit capture, delivered as 16-bit PCM WAV, with studio sessions held below a -50 dBFS noise floor
- First response within one working day; a scoped, fixed quote within two to three
These are the figures a delivery is measured against, not aspirations. A batch that misses them is re-recorded at our cost rather than repaired.
Frequently asked
How many Kannada speakers can you field?
500-1,500 speakers for a standard programme, fielded across 5 cities. Screen Bengaluru participants for native fluency and years of Karnataka residence; otherwise the cohort drifts towards second-language Kannada.
Do you transcribe Kannada in Kannada?
Yes, and we can deliver romanised or dual-script transcripts alongside. Northern lexical items replaced with standard equivalents is one of the rules fixed in the style guide before work begins.
Can you collect dialect-specific Kannada data?
Yes. Every speaker is tagged with region and dialect, so you can evaluate per variety after delivery instead of discovering the imbalance in production.
What about Kannada-English code-mixing?
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.
Request a Kannada dataset quote
Tell us the hours, speaker count and dialect spread you need. You get a scope, a timeline and a price.