Middle East & North Africa · Arabic (Perso-Arabic)
Persian Call Center Speech Dataset
Persian Call Center Speech delivered to your specification. A catalog entry, not a stock listing. This page covers what is specifically hard about this pairing, and which fields your specification needs to pin down.
Why Call Center Speech in Persian is its own problem
Persian written form and Tehran spoken form are far apart: in speech the verb endings change shape, pronouns shorten, and connected speech is the habit. A call center script is written in the standard language, but the caller opens their mouth in colloquial. Transcribing colloquial recordings against the written standard leaves text that does not match the audio, and the resulting transcript cannot be used for training.
The field to pin down first: Whether agent and caller are delivered on separate channels. Persian drops subject pronouns freely, so without a channel split the transcript cannot attribute an utterance to a speaker.
At a glance
| Language | Persian |
|---|---|
| Primary region | Middle East & North Africa |
| Writing system | Arabic (Perso-Arabic) |
| Category | Call Center Speech |
| Specification field to settle first | Whether agent and caller are delivered on separate channels. Persian drops subject pronouns freely, so without a channel split the transcript cannot attribute an utterance to a speaker. |
| Delivery | Sourced to order, pilot batch before the full run |
What Call Center Speech data is
Customer-service calls, simulated rather than intercepted, capturing both the agent and the caller side, used for call center QC, intent recognition, and dialogue systems.
What buyers get wrong about it
Compliance is what buyers fear most: call recordings involve personal data and recording consent, and the source has to be able to produce a consent provenance. This is also why we only do simulated collection and never work from intercepted real calls.
The specification field that decides the quote
Two-channel separated (agent and caller on separate tracks) or single-channel mixed. This directly determines how the data is annotated and how models are trained on it, and it has to be decided when the order is placed.
The language side: what Persian demands
Written Persian and spoken Tehrani Persian are far apart: verb endings, pronouns, and connected speech all shift in the colloquial form. Transcribing spoken recordings against the written form produces text that does not match the audio.
What we can put in this delivery
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Collection to your specification
Scripted or unscripted, in the language, domain and conditions your task needs. Specified separately where the variants need different contributor pools.
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Labels to your convention
Orthographic, phonetic or categorical, with the guideline written before production and shared with you for review.
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Contributor metadata
The attributes that let you slice the set rather than take it whole. The ones your task turns on, not a fixed list.
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Consent documentation
Signed contributor 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
File format, structure, segmentation and metadata schema set to your pipeline's requirements.
What arrives in a delivery
| Component | What it is |
|---|---|
| The data files | Format, structure and segmentation set to your pipeline. Named to a convention you specify. |
| Labels or transcription | Orthographic, phonetic or categorical, produced under a guideline you review before production starts. |
| Contributor metadata | The attributes that let you slice the set: age band, gender, region, dialect background, or whatever your task turns on. |
| Collection conditions | Environment, device and, where it can be measured, signal quality: recorded per file. |
| Annotation guideline | The document the annotators worked from, so you can reproduce the conventions on your own data. |
| Consent records | Signed contributor consent covering your intended use, plus cross-border transfer terms where they apply. |
| Collection methodology | How contributors 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 Persian Call Center Speech Dataset
How many distinct speakers can you provide for Persian Call Center Speech Dataset?
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. Whether agent and caller are delivered on separate channels. Persian drops subject pronouns freely, so without a channel split the transcript cannot attribute an utterance to a speaker.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Persian written form and Tehran spoken form are far apart: in speech the verb endings change shape, pronouns shorten, and connected speech is the 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 Persian Call Center Speech Dataset 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 Persian
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Persian 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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Persian 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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Persian 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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Persian 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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Persian Live Stream Speech
Long-session spoken content from live streams (host monologue and responses to audience interaction), unscripted and spoken quickly.
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Persian Voice Assistant
Command and dialogue data for voice assistants, usually with intent annotation, covering the full chain from wake word to understanding to response.
Request Persian Call Center Speech Dataset
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.
- You send the spec Language, hours, recording conditions, and the deadline.
- We reply within two business days A real number and a real timeline, not a range.
- You approve a pilot batch A small run first, so problems surface before the full order.
- Full run, then delivery with documents Audio, transcripts, and the consent record for every speaker.