High-quality, representative speech datasets across Africa’s diverse languages — collected with compliance, integrity, and scale.
Operational snapshot
Production-grade speech data, end-to-end
Collection → QA → validation → packaging, built for real deployment.
Coverage
10+ langs
Scale
5,000+ hrs
Delivered
Compliance
Verified
Consent + governance
Dataset build
Contributor ops
Managed onboarding, consent, and metadata capture at scale.
Quality signal
Multi-layer QA
Linguistic accuracy checks, integrity controls, and delivery packaging.
Built for AI teams shipping real models — from ASR and conversational AI to multilingual LLM training — our datasets reduce recognition errors, expand language coverage, and accelerate deployment across African markets.
Reduce WER in African accents
Improve recognition accuracy across regional dialects and code‑switching speech patterns using curated first‑language speakers and real‑world acoustic environments.
Deployment: Contact‑centre speech pipelines
Train multilingual voice and LLM models
Access diverse African speech data designed for modern ASR and generative AI workflows.
Deployment: Multilingual evaluation workflows
Launch voice AI in emerging markets
Build inclusive voice experiences using locally sourced speakers and authentic environments.
Deployment: Regional voice experiences
Evaluate and benchmark speech models
Test performance across accents, demographics, and acoustic environments.
Deployment: Model benchmarking pipelines
Scale contact‑centre automation
Train conversational AI with realistic multilingual call‑centre interactions.
Deployment: Conversational automation training
From large-scale multilingual collections to domain-specific datasets, we design and deliver production-ready speech data solutions.
Speech Collection
Field + onlineOnline and in-field collection across Africa using vetted first-language speakers.
Transcription & QA
Multi-layerDedicated language teams ensuring linguistic accuracy and metadata integrity.
Annotation & Packaging
ASR-readyStructured datasets adapted to client formats, model requirements, and ASR workflows.
We combine operational scale, structured governance, and production-ready workflows to deliver African speech datasets built for real-world AI systems.
01
Multi-layer QA, contributor management systems, and controlled workflows from collection through delivery.
02
Consent management, contributor transparency, and POPIA/GDPR-aligned data handling embedded into our processes.
03
Proven ability to manage thousands of contributors and deliver multi-thousand-hour datasets across languages.
04
Clean metadata, structured formats, version control, and packaging aligned to ASR and AI training pipelines.
A structured, transparent process designed to deliver compliant, production-ready speech datasets at scale.
Step 1
Prompt strategy, domain scoping, demographic targeting, and dataset specification before collection begins.
Step 2
Contributor onboarding, id verification, consent management, and structured recording execution.
Step 3
Structured error checks, compliance verification, and dataset integrity controls.
Step 4
Multi-layer linguistic review and metadata validation.
Step 5
Clean formatting, metadata structuring, and ASR-ready dataset preparation.
Step 6
Secure transfer, documentation, and version-controlled release.
Three pillars that define our approach to building inclusive, production-ready African speech data.
Built to support inclusive AI systems, our multilingual collections prioritise demographic balance, cultural authenticity, and technical readiness.
Through Africa Next Voices, we delivered 3,000 hours of high-quality speech data across multiple South African languages, combining operational discipline with community-driven authenticity.
A structured methodology guiding ethical, scalable, and production-ready African language dataset development from collection through quality assurance.
Partner with us to design, collect, and deliver multilingual speech datasets tailored to your AI objectives.
Next step
Talk to our team
Tell us your target languages, domain, and timeline—we’ll propose the right collection and QA strategy.
Response time typically within 1–2 business days.
