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Buy a Kannada spontaneous speech dataset

Speakers talk unscripted on prompted topics — describing a process, recounting an event, arguing a position — with a moderator who prompts but does not lead. Available for Kannada as a licensed build against your specification, with audio, verbatim transcripts, speaker metadata and consent records.

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Structured dataset packages ready for delivery — Buy a Kannada spontaneous speech dataset
Language
Kannada (Kannada)
Type
Spontaneous Speech
Per speaker
25–40 minutes of accepted audio per speaker
Accepted yield
60–70% of recorded time is accepted
01

How Kannada spontaneous speech is recorded

Speakers talk unscripted on prompted topics — describing a process, recounting an event, arguing a position — with a moderator who prompts but does not lead.

A 60-minute session covering six to eight topics, recorded continuously and segmented afterwards into utterances at natural pause boundaries.

60–70% of recorded time is accepted. Long silences, moderator speech and abandoned topics are cut in post, so recorded hours run well ahead of delivered hours. Budget for the gap.

Share of recorded time that passes QAScripted8590%Spontaneous6070%Conversational5565%Telephony5060%Budget from delivered hours, not studio hours — the gap is the whole difference.
02

What is in the package

  • 16-bit PCM WAV audio, captured at 48 kHz / 24-bit and delivered at your target rate
  • Verbatim Kannada transcripts with utterance-level timestamps
  • Filled-pause and false-start markers
  • Segment offsets into the parent session file
  • Topic label per segment
  • Speech-rate and pause-density statistics per speaker
  • Per-speaker metadata: age band, gender, region, dialect, education band, device
  • Consent records mapped to speaker IDs and retained for audit
  • Speaker-disjoint train / dev / test splits
Audio QC engineer inspecting waveforms and spectrograms — supporting buy a kannada spontaneous speech dataset
Audio QC engineer inspecting waveforms and spectrograms
03

Specification

FieldStandard value
LanguageKannada (kn-IN)
Speech typeSpontaneous Speech
Per speaker25–40 minutes of accepted audio per speaker
File granularitySession-length WAV plus segmented utterance files with offsets into the parent
SegmentationPause-boundary segmentation, reviewed by a native listener rather than left to VAD
Moderator channelRecorded separately and excluded from the delivered speaker audio
Disfluency conventionFilled pauses, repetitions and false starts transcribed, not normalised away
Dialects coveredBangalore urban, Mysuru (standard literary), Dharwad / North Karnataka, Mangaluru coastal
Recording citiesBengaluru, Mysuru, Hubballi-Dharwad, Mangaluru
TranscriptionNative verbatim, second-pass reviewed
04

Quality gates applied to spontaneous speech

The failure modes this style is prone to: speakers who dry up after a minute, leaving sessions that look complete by duration but are mostly silence

  • Segment boundary review — bad boundaries produce truncated words that poison training more than they help
  • Disfluency transcription consistency audited across transcribers, since conventions drift fast on this style
  • Moderator speech confirmed absent from delivered segments
  • Topic distribution checked per speaker so one dominant subject does not skew the language model
05

Pricing and volumes

VolumeIndicative rangeDelivery
50 hours (pilot-scale)₹2,10,000 – ₹4,10,0003-4 weeks
250 hours₹9,97,500 – ₹19,47,5005-8 weeks
1,000 hours₹35,70,000 – ₹69,70,00010-16 weeks

Bands, not a price list. A signed specification converts them into one fixed figure, and staged delivery lets you start training before the full corpus lands.

06

Why generic Kannada corpora underperform

Mysuru/Bengaluru standard dominates. North Karnataka (Dharwad, Kalaburagi) and coastal Mangaluru speech are barely represented in any public corpus.

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.

  • 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
07

Licensing and compliance

  • Perpetual, transferable licence covering model training, derivative models and commercial deployment
  • Written informed consent from every speaker, retained and auditable
  • Compliant with India's DPDP Act 2023 handling requirements and mapped to GDPR obligations for EU buyers
  • No scraped, resold or re-licensed third-party audio in any delivery
08

How buying works

  • Send your specification or use the standard one above
  • Receive a fixed scope, price and delivery schedule within one working day
  • Optional paid pilot of 10-20 hours against the same spec
  • Recruitment and recording begin on signature, with staged batches
  • Acceptance testing per batch, then final delivery with the full manifest

Frequently asked

Can I buy an off-the-shelf Kannada spontaneous speech dataset today?

We build to specification rather than reselling a fixed corpus, because off-the-shelf Kannada audio almost never matches a real deployment's dialect mix and noise profile. A 50-hour build ships in three to four weeks.

What licence do we get?

A perpetual, transferable licence with full IP transfer on delivery. You can train, distribute and commercialise models built on the data without further payment.

Can we get a free sample?

Yes — a short sample reflecting the agreed specification is provided before the pilot is signed, so you can check transcript quality and audio characteristics.

Which Kannada dialects are included?

By default Bangalore urban, Mysuru (standard literary), Dharwad / North Karnataka and others, with quotas set at recruitment. You can weight the mix to match where your product is deployed.

Related pages

Quote this Kannada dataset

Tell us the volume and dialect mix for Kannada spontaneous speech and you get a fixed price and delivery date.

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