South Asia · Sinhala
Sinhala Noisy Speech Dataset
Sinhala 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 Sinhala is its own problem
Sinhala in noise carries a higher share of English loanwords — speakers raise their volume to cut through and simplify what they say — which in turn makes language-component judgment more disputable. The annotation guideline has to handle this.
The field to pin down first: Measure the loanword share in noisy conditions and compare it against a quiet-environment baseline, with the difference explained.
At a glance
| Language | Sinhala |
|---|---|
| Primary region | South Asia |
| Writing system | Sinhala |
| Category | Noisy Speech |
| Specification field to settle first | Measure the loanword share in noisy conditions and compare it against a quiet-environment baseline, with the difference explained. |
| 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 Sinhala demands
Everyday Sinhala conversation is heavily embedded with English words, especially in the Colombo urban belt. Treating this mixed speech as pure Sinhala strips out high-frequency loanwords as if they were errors.
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 Sinhala Noisy Speech
How many distinct speakers can you provide for Sinhala 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. Measure the loanword share in noisy conditions and compare it against a quiet-environment baseline, with the difference explained.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Sinhala in noise carries a higher share of English loanwords — speakers raise their volume to cut through and simplify what they say — which in turn makes language-component judgment more disputable. 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 Sinhala 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 Sinhala
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Sinhala Speech Translation
Parallel data pairing source-language audio with target-language translation, used for speech-to-text and speech-to-speech translation models.
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Sinhala In-the-Wild Speech
Speech collected under fully natural conditions — no studio, no topic constraints — as close to real usage as collection gets.
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Sinhala Call Center Speech
Recorded customer-service calls, real or simulated, capturing both the agent and the caller side, used for call center QC, intent recognition, and dialogue systems.
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Sinhala Conversational Speech
Speech from natural conversation between two or more people, on open or semi-structured topics, used for conversational AI, voice assistants, and small talk models.
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Sinhala Singing Voice
Vocal recordings with melody, in both a cappella and accompanied form, used for singing voice synthesis, music information retrieval, and lyric alignment.
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Sinhala Speech Commands
Targeted recordings of short command words or phrases, usually with many speakers reading each entry several times over, used for wake words and on-device command recognition.
Noisy Speech in other languages
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Punjabi Noisy Speech
South Asia
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Burmese Noisy Speech
Southeast Asia
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Amharic Noisy Speech
Sub-Saharan Africa
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Ukrainian Noisy Speech
Europe
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Swahili Noisy Speech
Sub-Saharan Africa
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Kurdish Noisy Speech
Middle East & North Africa
Request Sinhala 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.