Middle East & Europe · Latin
Turkish Elderly Voice Dataset
Turkish elderly voice 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 elderly voice in Turkish is its own problem
Older Turkish speakers use more traditional vocabulary — they make little use of the coinages from the language-purification period and retain more Ottoman-era loanwords instead. That leaves their vocabulary distribution clearly different from younger speakers', and it needs to be annotated.
The field to pin down first: Record each speaker's era of schooling and vocabulary preference, to explain the differences in vocabulary distribution.
At a glance
| Language | Turkish |
|---|---|
| Primary region | Middle East & Europe |
| Writing system | Latin |
| Category | Elderly Voice |
| Specification field to settle first | Record each speaker's era of schooling and vocabulary preference, to explain the differences in vocabulary distribution. |
| Delivery | Sourced to order, pilot batch before the full run |
What elderly voice data is
Speech data from elderly speakers, usually stratified by age band and health status, used for voice products built for older users.
What buyers get wrong about it
Speaking rate, volume, and articulation vary enormously across elderly speakers, and recruiting them is hard. Too small a sample and the model simply skews toward younger users.
The specification field that decides the quote
Age stratification and whether speakers with speech disorders are included must be stated up front.
The language side: what Turkish demands
Turkish is an agglutinative language: one root can carry a long chain of suffixes, so the word list explodes. Istanbul and eastern accents also differ noticeably — if speaker origin is not recorded clearly, model generalization suffers.
What we can put in this delivery
-
Read and conversational speech
Scripted recording for TTS, and unscripted conversation for recognition. Specified separately because they need different speaker pools.
-
Transcription to your convention
Orthographic or phonetic, with the guideline written before production and shared with you for review.
-
Speaker metadata
Age band, gender, region and dialect background per file, so you can slice the dataset rather than take it whole.
-
Consent documentation
Signed speaker consent covering the intended use, plus collection methodology and the annotation guideline.
-
Pilot batch
A small batch first, which you can reject. Misalignments surface after a few hours rather than at delivery.
-
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 Turkish Elderly Voice
How many distinct speakers can you provide for Turkish Elderly Voice?
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. Record each speaker's era of schooling and vocabulary preference, to explain the differences in vocabulary distribution.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Older Turkish speakers use more traditional vocabulary — they make little use of the coinages from the language-purification period and retain more Ottoman-era loanwords instead. 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 Turkish Elderly Voice 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 Turkish
-
Turkish Audiobook
Continuous long-form narration in audiobook style, steady in intonation and generous in duration, the main source material for high-quality TTS.
-
Turkish Short Video Speech
Speech in the talking-head style of short video — fast, emotionally strong, colloquial — used for short video subtitles and content understanding.
-
Turkish Live Stream Speech
Long-session spoken content from live streams — host monologue and responses to audience interaction — fast-paced and heavily improvised.
-
Turkish Voice Assistant
Command and dialogue data for voice assistants, usually with intent annotation, covering the full chain from wake word to understanding to response.
-
Turkish Accented English
English speech from non-native speakers or specific regional accents, grouped by accent origin, used to improve accent robustness in ASR.
-
Turkish Speech Translation
Parallel data pairing source-language audio with target-language translation, used for speech-to-text and speech-to-speech translation models.
Elderly Voice in other languages
-
Arabic (Egyptian) Elderly Voice
Middle East & North Africa
-
Arabic (Gulf) Elderly Voice
Middle East & North Africa
-
Kannada Elderly Voice
South Asia
-
Punjabi Elderly Voice
South Asia
-
Burmese Elderly Voice
Southeast Asia
-
Amharic Elderly Voice
Sub-Saharan Africa
Request Turkish Elderly Voice
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.