Evaluate AI Voice Quality for African Languages
Help researchers improve text-to-speech technology by rating how natural AI-generated speech sounds. Anonymous, fast, and impactful.
31+
Evaluations Completed
All
African Languages Supported
~2 min
Average Per Sample
100%
Open Source
How It Works
Three simple steps to contribute to groundbreaking research
Listen
Put on headphones and listen to short audio clips generated by AI text-to-speech systems.
Rate
Rate each clip on a scale of 1–5 based on how natural and human-like the speech sounds to you.
Contribute
Your anonymous ratings help researchers compare TTS models and improve voice tech for African languages.
Everything You Need
A complete platform for collecting MOS evaluations at scale
Audio Evaluation
Listen to AI-generated speech samples and rate how natural they sound on a standardized MOS scale.
Real-time Analytics
Track evaluation progress, MOS distributions, and inter-rater agreement with a powerful admin dashboard.
Anonymous & Secure
All evaluations are fully anonymous. No accounts required. Data is stored securely and used only for research.
Mobile Optimized
Evaluate from any device — phone, tablet, or desktop. Touch-friendly interface with optimized audio playback.
Multi-Language
Built for underrepresented African languages. Easily extensible to support new languages and dialects.
Open Source
Fully open source and community-driven. Inspect, modify, and contribute to the platform on GitHub.
Powerful Admin Dashboard
Manage your entire evaluation study from one clean interface. Upload audio, monitor progress, and export publication-ready data.
- Real-time MOS score distributions and analytics
- Audio sample management with multi-model support
- Rater demographics and completion tracking
- One-click data export for academic papers
Supports All African Languages
We're seeking native speakers to help evaluate AI speech quality across all underrepresented languages on the African continent
Luganda
Uganda
10M+ speakers
Krio
Sierra Leone
6M+ speakers
All African Languages
Entire Continent
2000+ languages
Trusted by Researchers
What researchers and evaluators are saying about OpenMOS
“OpenMOS made it incredibly easy for us to collect MOS evaluations from native Luganda speakers. The data quality is excellent.”
Dr. Sarah Nakamya
NLP Researcher, Makerere University
“As a native Krio speaker, I loved how simple and accessible the evaluation process was. It took me less than 15 minutes.”
Mohamed Kamara
Native Speaker Evaluator
“The admin dashboard gives us all the analytics we need — MOS distributions, rater demographics, and model comparisons in one place.”
Prof. James Ochieng
Speech Technology Lab Lead
Ready to Make an Impact?
Your voice matters. Help us build better speech technology for millions of African language speakers.