South Asia · Kannada
Kannada Noisy Speech Dataset
Kannada noisy speech sourced to your specification — no inventory, no fixed listing. This page covers what is specifically hard about this pairing, and which fields your specification needs to pin down.
Why noisy speech in Kannada is its own problem
Karnataka's noisy scenes — markets, bus stands, street junctions — share a property a generic noise library cannot reproduce: much of the competing sound is other people talking in Kannada. Speech-on-speech interference behaves differently from mechanical noise: it competes for the same phonetic content rather than masking it from outside, so the target speaker cannot be separated by frequency or level, and the competing words are close enough to the target language to be mistaken for the speaker's own. A market recording is a different product from a traffic recording, even at equal SNR.
The field to pin down first: Classify each file's noise by type and state whether it contains intelligible speech; where it does, annotate the competing speech or exclude the file — one SNR figure does not distinguish traffic from a crowd talking.
At a glance
| Language | Kannada |
|---|---|
| Primary region | South Asia |
| Writing system | Kannada |
| Category | Noisy Speech |
| Specification field to settle first | Classify each file's noise by type and state whether it contains intelligible speech; where it does, annotate the competing speech or exclude the file — one SNR figure does not distinguish traffic from a crowd talking. |
| Delivery | Sourced to order, pilot batch before the full run |
What noisy speech data is
Speech collected under background noise — street, in-car, restaurant, office and other real environments — used for noise-robust models and speech enhancement.
What buyers get wrong about it
Noise type has to be reproducible. Buyers do not want vaguely noisy; they want a specified condition like restaurant chatter at 5 dB SNR.
The specification field that decides the quote
Signal-to-noise ratio (SNR) level and noise type must be annotated per file, or the data cannot be reproduced.
The language side: what Kannada demands
Kannada has more than a dozen regional dialects, but only a few have a written tradition. That rules out transcribing dialect speech against a standard script, so the specific dialects to be collected have to be fixed first.
What we can put in this delivery
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Read and conversational speech
Scripted recording for TTS, and unscripted conversation for recognition. Specified separately because they need different speaker pools.
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Transcription to your convention
Orthographic or phonetic, with the guideline written before production and shared with you for review.
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Speaker metadata
Age band, gender, region and dialect background per file, so you can slice the dataset rather than take it whole.
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Consent documentation
Signed speaker consent covering the intended use, plus collection methodology and the annotation guideline.
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Pilot batch
A small batch first, which you can reject. Misalignments surface after a few hours rather than at delivery.
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Delivery in your format
Audio format, sampling rate, segmentation length and metadata schema set to your pipeline's requirements.
What arrives in a delivery
| Component | What it is |
|---|---|
| Audio files | Format, sampling rate and segmentation length set to your pipeline. Named to a convention you specify. |
| Transcription | Orthographic or phonetic, produced under a guideline you review before production starts. |
| Speaker metadata | Age band, gender, region and dialect background per file, plus a speaker identifier so the dataset can be sliced. |
| Recording conditions | Environment, device and, where relevant, measured signal-to-noise ratio per file. |
| Annotation guideline | The document the annotators worked from, so you can reproduce the conventions on your own data. |
| Consent records | Signed speaker consent covering your intended use, with the transfer mechanism addressed where required. |
| Collection methodology | How speakers were recruited, screened and scheduled — the part that tells you how biased the pool is. |
| Quality report | Pilot outcome, re-work log, and the annotator agreement figures where the task supports measuring them. |
Questions we get about Kannada Noisy Speech
How many distinct speakers can you provide for Kannada Noisy Speech?
It depends on the specification and the timeline, and we will give a real number rather than a target. For this pairing, speaker recruitment is usually the step that sets the schedule. Classify each file's noise by type and state whether it contains intelligible speech; where it does, annotate the competing speech or exclude the file — one SNR figure does not distinguish traffic from a crowd talking.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Karnataka's noisy scenes — markets, bus stands, street junctions — share a property a generic noise library cannot reproduce: much of the competing sound is other people talking in Kannada. That is exactly the kind of decision a default guideline leaves open, and it is where annotators diverge. Send us your guideline, or we will draft one and you can review it before production starts.
Do you offer a sample before we commit to a full run?
Yes. Select a free sample in the request form and describe what you need. A pilot batch is the cheapest way to establish whether the quality bar is reachable for Kannada Noisy Speech before committing to the full volume.
Is the data licensed or owned outright?
Licensing terms are set per project, so tell us how the model will be used and whether it will be distributed. Consent documentation travels with the data either way, and we do not handle medical or clinical data or recorded telephone calls.
Other datasets in Kannada
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Kannada Code-Switching Speech
Speech that mixes two or more languages inside a single utterance — Hinglish, Spanglish, Taglish — used for recognition in real spoken settings.
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Kannada Children Speech
Speech data from child speakers, grouped by age band, used for children's speech recognition and children's education products.
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Kannada Audiobook
Continuous long-form narration in audiobook style, steady in intonation and generous in duration, the main source material for high-quality TTS.
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Kannada Short Video Speech
Speech in the talking-head style of short video — fast, emotionally strong, colloquial — used for short video subtitles and content understanding.
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Kannada Live Stream Speech
Long-session spoken content from live streams — host monologue and responses to audience interaction — fast-paced and heavily improvised.
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Kannada Voice Assistant
Command and dialogue data for voice assistants, usually with intent annotation, covering the full chain from wake word to understanding to response.
Noisy Speech in other languages
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Bangla Noisy Speech
South Asia
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Khmer Noisy Speech
Southeast Asia
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Arabic (Egyptian) Noisy Speech
Middle East & North Africa
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Arabic (Gulf) Noisy Speech
Middle East & North Africa
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Punjabi Noisy Speech
South Asia
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Burmese Noisy Speech
Southeast Asia
Request Kannada Noisy Speech
Tell us the language, the hours, and what the data needs to look like. You will get a real number and a real timeline — not a range. If we cannot source it well, we will tell you that instead.
- Pilot batch before the full run, so problems surface early.
- Consent documentation delivered with the data.
- No medical or clinical data. No recorded telephone calls.