Closing the Digital Gap for the Somali Language
Open-source language technology for 20+ million Somali speakers worldwide
Why Somali Needs Language Technology
When AI doesn't understand Somali, 20 million speakers are excluded from the digital revolution
Only 100 Languages Have AI Support
While English, Mandarin, and Spanish dominate AI development, thousands of languages—including Somali—are systematically excluded. Siri doesn't understand Somali. Google Translate struggles with dialect variations. ChatGPT can't process Somali context properly.
The Somali Language Deserves Better
Spoken across Somalia, Somaliland, Djibouti, Ethiopia's Somali Region, Kenya's North Eastern Province, and diaspora communities in North America, Europe, and the Middle East—Somali is a living, vibrant language rich in dialectal diversity. Yet it lacks basic NLP infrastructure.
The Real-World Impact
Why can't Somali students access educational content in their mother tongue? Why can't governments analyze citizen feedback in Somali? Why do businesses struggle to serve Somali-speaking customers? The absence of language technology isn't just inconvenient—it's a barrier to progress.
Somali NLP Is Changing That
We're a non-profit research initiative dedicated exclusively to Somali language technology. Through rigorous research, open-source collaboration, and African-hosted infrastructure, we're building the NLP resources that will enable the Somali language to thrive in the AI age. But solving this challenge requires more than good intentions—it requires rigorous research methodology and transparent practices.
Our Research Approach
Building robust language technology for the Somali language requires rigorous data engineering, transparent research methodologies, and community collaboration. As a non-profit research initiative, we prioritize scientific integrity and reproducibility over commercial speed.
Data Engineering First
Clean data beats clever algorithms
- ▸Multi-Source AggregationWikipedia (15+ language editions), BBC Somali service, HuggingFace datasets, and academic corpora
- ▸Intelligent Deduplication95% duplicate removal using MinHash LSH (locality-sensitive hashing) for fuzzy matching across spelling variations
- ▸Quality ValidationAutomated checks for encoding issues, dialect consistency, content toxicity, and source provenance
- ▸Transparent ProvenanceEvery data point traced to source with metadata—no black-box aggregation
- ▸Scalable PipelinesBuilt to grow from 130K to millions of records as the ecosystem expands
Open Science
Reproducible, auditable, community-driven
- ▸Open DatasetsAll datasets published under open licenses on HuggingFace
- ▸Open-Source CodeModel training code, pipelines, and evaluation frameworks on GitHub
- ▸Transparent BenchmarkingWe publish successes AND failures—real science requires honesty
- ▸Community ContributionsIssues, pull requests, and research collaborations welcome
- ▸Documentation-FirstEvery decision explained, every method justified, every assumption stated
Data Sovereignty
African data, hosted in Africa, governed by Africans
- ▸African InfrastructureModels and datasets hosted on African servers—no data extraction to Silicon Valley
- ▸Local GovernanceGovernance frameworks designed with Somali stakeholders, not imposed externally
- ▸Privacy-PreservingDefault privacy settings, no surveillance capitalism business model
- ▸Long-Term SustainabilityA non-profit commitment to Somali language technology—no exit strategies, no pivots, just sustained research infrastructure
- ▸Anti-Colonial TechRejecting extractive models where African data enriches foreign corporations
These principles guide everything we build. Our flagship project demonstrates this methodology in action.
Our Research Projects
Our research approach translates into concrete projects. Starting with the Somali Dialect Classifier, we're building a comprehensive suite of NLP resources—all open-source, African-hosted, and developed in collaboration with Somali linguists and researchers.
Current Research
Somali Dialect Classifier
Identifying Benaadir, Northern (Waqooyi), and Maay dialects
Our flagship project: a comprehensive dataset and classifier for Somali dialect identification. Aggregating text from Wikipedia, BBC Somali, HuggingFace, and academic corpora, this dataset will enable dialect-aware NLP applications. Future work includes benchmark suites, language models, and evaluation frameworks—all developed collaboratively with the Somali research community.
Our long-term research vision focuses on three impact areas:
Digital Inclusion
When Somali language technology matures, digital services become accessible to millions currently excluded. From mobile banking to e-commerce, applications can finally serve Somali speakers in their native language without forcing them to learn English or Arabic.
Educational Equity
Students learning in Somali shouldn't be disadvantaged in the digital age. Robust NLP enables automatic captioning, reading assistance, and intelligent tutoring systems—helping Somali-medium education compete with English-medium alternatives.
Effective Governance
Governments can better serve citizens when they can process feedback in Somali. From analyzing public comments to extracting insights from citizen surveys, NLP tools enable data-driven governance in the language people actually speak.
This is a long-term research commitment—not a quick commercial project. As Somali NLP infrastructure matures, it will enable an ecosystem where researchers propose new projects, developers build applications, and institutions serve communities more effectively. Our goal is to make Somali language technology as robust as major world languages, setting a standard for other under-resourced languages.
Join the Research Collaboration
Somali NLP welcomes researchers, linguists, developers, and community members. Whether you want to contribute datasets, propose research projects, or validate our work—there's a place for you in building Somali language technology.
Get InvolvedContact Information
Join Our Research Community
Somali NLP is a collaborative, non-profit initiative. We welcome researchers, linguists, developers, and community validators who share our mission.
Academic Researchers
Collaborate on papers, propose research projects, or access datasets for low-resource NLP research
Discuss ResearchOpen-Source Contributors
Improve datasets, build evaluation tools, contribute dialect knowledge, or validate data quality
View on GitHubInstitutional Partners
Universities, government agencies, and NGOs interested in Somali language technology development
Explore Partnership