Sub-Saharan Africa · Latin
Swahili Code-Switching Speech Dataset
Swahili Code-Switching 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 Code-Switching Speech in Swahili is its own problem
Swahili code-switching is not one phenomenon but two, and they belong to different countries. In Nairobi, English is inserted so heavily that it produces Sheng, a Swahili-English-local-language mix that young speakers use as an everyday register, and whole clauses can switch. In Dar es Salaam the Swahili stays much purer, English appears far less often, and the mixing that does occur is with local languages instead. A switch-point convention written for the Nairobi pattern will mislabel Dar es Salaam recordings, and the reverse is just as true.
The field to pin down first: State which mixing pattern the batch targets (Swahili-English / Swahili with a local language / Sheng) and annotate switch points at word level with a language label per token. The three patterns cannot share one annotation scheme.
At a glance
| Language | Swahili |
|---|---|
| Primary region | Sub-Saharan Africa |
| Writing system | Latin |
| Category | Code-Switching Speech |
| Specification field to settle first | State which mixing pattern the batch targets (Swahili-English / Swahili with a local language / Sheng) and annotate switch points at word level with a language label per token. The three patterns cannot share one annotation scheme. |
| Delivery | Sourced to order, pilot batch before the full run |
What Code-Switching Speech data is
Speech that mixes two or more languages inside a single utterance (Hinglish, Spanglish, Taglish), used for recognition in real spoken settings.
What buyers get wrong about it
The switch point is the hard part, where language A gives way to B inside a sentence, different annotators can place it several words apart. The guideline has to be fixed before annotation starts.
The specification field that decides the quote
Whether annotation marks word-level switch points or only tags the language of the whole utterance. The workload differs by a multiple.
The language side: what Swahili demands
Swahili has few native speakers; the large majority of its users speak it as a second language, with accents shaped heavily by their first languages. Standard Tanzanian Swahili and the Kenyan coastal dialects also differ, so speaker background has to be documented.
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 Swahili Code-Switching Speech Dataset
How many distinct speakers can you provide for Swahili Code-Switching 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. State which mixing pattern the batch targets (Swahili-English / Swahili with a local language / Sheng) and annotate switch points at word level with a language label per token. The three patterns cannot share one annotation scheme.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Swahili code-switching is not one phenomenon but two, and they belong to different countries. 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 Swahili Code-Switching 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 Swahili
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Swahili 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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Swahili 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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Swahili 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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Swahili 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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Swahili Call Center Speech
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.
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Swahili 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.
Request Swahili Code-Switching 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.