ASR datasets · ಕನ್ನಡ
Kannada ASR Training Data
Transcribed speech corpora built to train and evaluate automatic speech recognition, with verbatim transcription, timestamps and per-token language tagging where code-mixing occurs. This page covers how that works specifically for Kannada, where north karnataka speech has markedly different intonation and lexicon from mysuru standard.
- Language
- Kannada (kn-IN)
- Dialects covered
- 5
- Typical programme
- 250-1,000 hours
- Cities
- Bengaluru, Mysuru, Hubballi-Dharwad
What changes when the language is Kannada
The service specification stays constant across languages; the linguistics do not. For Kannada, three things drive the design of a asr datasets programme.
- North Karnataka speech has markedly different intonation and lexicon from Mysuru standard
- Dialect spread: 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.
Technical specification
| Parameter | Standard |
|---|---|
| Audio | 16 kHz or 48 kHz PCM WAV |
| Transcription | Verbatim, including disfluencies, false starts and fillers |
| Timestamps | Utterance level by default; word level on request |
| Tagging | Noise, overlap, unintelligible, foreign-language and code-switch tags |
| Normalisation | Raw and normalised text columns delivered separately |
| Split | Train/dev/test splits with no speaker leakage across splits |
Kannada cohort design
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 |
Process
- Style guide authored per language, covering numerals, loanwords, script and disfluency rules
- Transcriber calibration round with inter-annotator agreement measurement
- First-pass transcription
- Second-pass native review
- Automated consistency checks against the style guide
- Split generation with speaker-disjoint partitions
Kannada-specific quality rules
- 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
Agreement is measured, not assumed. We report word-level agreement on a held-out sample so you can judge label quality before training on it.
Deliverables
- Audio plus aligned transcripts (JSON/TSV, or your schema)
- Style guide as delivered documentation
- Inter-annotator agreement report
- Speaker-disjoint train/dev/test splits
Worked example
A representative Kannada asr datasets engagement: 250 hours from 500 speakers, 50/50 gender, ages 18-45, spread across Bengaluru, Mysuru, Hubballi-Dharwad, recorded to the specification above and delivered in WAV with a per-utterance manifest.
Timeline: Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
Where this data is missing today
Mysuru/Bengaluru standard dominates. North Karnataka (Dharwad, Kalaburagi) and coastal Mangaluru speech are barely represented in any public corpus.
Frequently asked
How much does Kannada asr datasets cost?
Priced per delivered hour or unit against a written spec. The cost drivers for Kannada are dialect spread, demographic narrowness and recording condition, in that order.
Which Kannada dialects are included?
By default Bangalore urban, Mysuru (standard literary), Dharwad / North Karnataka, Mangaluru coastal and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.
Can you deliver Kannada data in our format?
Yes. Audio plus aligned transcripts (JSON/TSV, or your schema) is the default, but naming, schema and directory structure follow your pipeline.
How long does a Kannada programme take?
Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
Request a Kannada asr datasets quote
Hours, speakers, dialects, deadline. Send what you have.