Central Asia & Caucasus · Latin
Uzbek Podcast Speech Dataset
Uzbek podcast 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 podcast speech in Uzbek is its own problem
Uzbek podcasts skew toward interview formats, and guests come from different generations and different countries — a Tashkent host may interview a guest schooled in Cyrillic-era Uzbek, or a speaker from Afghanistan whose Uzbek carries Dari influence and a different script habit. Across a long episode that layering accumulates, and a single language label for the whole episode tells a buyer nothing about what is inside it.
The field to pin down first: Annotate each speaker's country of origin, generation, and script of schooling, segment by segment — long-form Uzbek audio routinely mixes speakers whose Uzbek is not the same Uzbek.
At a glance
| Language | Uzbek |
|---|---|
| Primary region | Central Asia & Caucasus |
| Writing system | Latin |
| Category | Podcast Speech |
| Specification field to settle first | Annotate each speaker's country of origin, generation, and script of schooling, segment by segment — long-form Uzbek audio routinely mixes speakers whose Uzbek is not the same Uzbek. |
| Delivery | Sourced to order, pilot batch before the full run |
What podcast speech data is
Long-form podcast and interview audio, either solo monologue or two-person conversation, used for long-form speech recognition and speaker modeling.
What buyers get wrong about it
Copyright and transcription quality are the two big traps with podcast material. Public podcasts cannot be used commercially as they are; you either license them or record original content.
The specification field that decides the quote
Whether speaker diarization annotation is required — it is the most labor-intensive item in long-form audio.
The language side: what Uzbek demands
Uzbek is officially written in Latin script, but a large share of existing corpora is in Cyrillic. The conversion rules between the two leave a few letters without a clean one-to-one mapping, so conversion introduces 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 Uzbek Podcast Speech
How many distinct speakers can you provide for Uzbek Podcast 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. Annotate each speaker's country of origin, generation, and script of schooling, segment by segment — long-form Uzbek audio routinely mixes speakers whose Uzbek is not the same Uzbek.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Uzbek podcasts skew toward interview formats, and guests come from different generations and different countries — a Tashkent host may interview a guest schooled in Cyrillic-era Uzbek, or a speaker from Afghanistan whose Uzbek carries Dari influence and a different script habit. 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 Uzbek Podcast 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 Uzbek
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Uzbek Elderly Voice
Speech data from elderly speakers, usually stratified by age band and health status, used for voice products built for older users.
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Uzbek Accented English
English speech from non-native speakers or specific regional accents, grouped by accent origin, used to improve accent robustness in ASR.
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Uzbek 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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Uzbek 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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Uzbek 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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Uzbek 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.
Podcast Speech in other languages
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Vietnamese Podcast Speech
Southeast Asia
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Filipino Podcast Speech
Southeast Asia
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Persian Podcast Speech
Middle East & North Africa
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Tamil Podcast Speech
South Asia
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Telugu Podcast Speech
South Asia
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Malayalam Podcast Speech
South Asia
Request Uzbek Podcast 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.