Yoruba
Text, speech, and dialect-sensitive pipeline support.
AfriLang is designed to grow from high-priority language support into a broader African language infrastructure layer with domain-specific and dialect-aware depth.
The current list reflects strategic starting points for language infrastructure, model training, and regional deployment across key African markets.
Text, speech, and dialect-sensitive pipeline support.
Language resources positioned for translation and speech tasks.
Scalable support for voice interfaces and multilingual applications.
Regional utility across search, assistant, and education products.
Foundation for East African language tooling and model expansion.
Prepared for future corpus growth and model coverage extensions.
Each language requires data collection strategy, orthography handling, dialect review, domain adaptation, and long-term validation. AfriLang treats language expansion as infrastructure work, not surface-level localization.
Corpora, parallel text, named entities, terminology, normalization, and search support for written language systems.
Speaker diversity, transcription quality, recording variation, pronunciation coverage, and dialect metadata for speech models.
Language-specific benchmarks and review loops that reflect real use, not only borrowed metrics from high-resource languages.
Universities, language communities, institutions, and private partners can contribute to roadmap growth and dataset quality.
The roadmap can grow by market demand, strategic partnerships, and data availability, while preserving quality standards for each language added.
Language expansion is guided by ecosystem demand, quality of available resources, institutional partnerships, and the feasibility of building reliable evaluation pipelines.
Priority goes to languages with strong utility across communication, commerce, education, and public service delivery.
Expansion is stronger where text, audio, annotation support, and linguistic expertise can sustain model quality.
Collaborations with communities, universities, and institutions improve both coverage and long-term trust.