Southeast Asia · Khmer
Khmer Noisy Speech Dataset
Khmer 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 Khmer is its own problem
The hard part of annotating Khmer in noise is that the existing mismatch between orthography and pronunciation gets magnified — when the audio is unclear it is that much harder to decide which letter to write. Annotators need extra decision rules to lean on.
The field to pin down first: Khmer carries its lexical load in consonants rather than in tone, so noise attacks exactly the distinction the transcript depends on — fix an uncertainty convention instead of letting annotators guess.
At a glance
| Language | Khmer |
|---|---|
| Primary region | Southeast Asia |
| Writing system | Khmer |
| Category | Noisy Speech |
| Specification field to settle first | Khmer carries its lexical load in consonants rather than in tone, so noise attacks exactly the distinction the transcript depends on — fix an uncertainty convention instead of letting annotators guess. |
| 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 Khmer demands
Khmer script has no spaces between words, and it contains many letters that are written but not pronounced. The transcription convention has to be set first: write as spelled (orthographic) or write as spoken (phonemic). Data produced under the two conventions cannot be mixed.
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 Khmer Noisy Speech
How many distinct speakers can you provide for Khmer 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. Khmer carries its lexical load in consonants rather than in tone, so noise attacks exactly the distinction the transcript depends on — fix an uncertainty convention instead of letting annotators guess.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. The hard part of annotating Khmer in noise is that the existing mismatch between orthography and pronunciation gets magnified — when the audio is unclear it is that much harder to decide which letter to write. 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 Khmer 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 Khmer
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Khmer 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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Khmer 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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Khmer 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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Khmer 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.
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Khmer Read Speech
Recordings of speakers reading specified text, with clear pronunciation and known text, the base material for TTS and ASR.
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Khmer Podcast Speech
Long-form podcast and interview audio, either solo monologue or two-person conversation, used for long-form speech recognition and speaker modeling.
Noisy Speech in other languages
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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
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Hausa Noisy Speech
Sub-Saharan Africa
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Uzbek Noisy Speech
Central Asia & Caucasus
Request Khmer 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.