Introduction
Somalia’s rich linguistic landscape plays a central role in communication, governance, education, and social cohesion. However, limited digital resources for the Somali language have constrained its representation in modern AI systems and digital services. Strengthening Natural Language Processing (NLP) capacity for Somali is therefore essential for digital inclusion and effective technology adoption.
The Natural Language Processing for Somalia project focuses on developing AI-driven language technologies that enable computers to understand, process, and generate Somali language text and speech. Led by the SIMAD AI Institute, the project aims to advance locally relevant NLP solutions that support public services, research, and digital innovation.
Explaining the Science
The project applies machine learning and deep learning methods commonly used in NLP, including statistical language modeling and neural-network-based approaches. These techniques allow AI systems to learn linguistic structure, meaning, and context from data.
By focusing on low-resource language methods, the project addresses challenges specific to Somali, such as limited annotated data and linguistic variation. This ensures that the resulting models are robust, ethically developed, and suitable for real-world deployment.
Project Aims
The project aims to:
- Strengthen Somali-language AI and digital inclusion
- Develop foundational NLP tools for Somali text and speech
- Support AI applications in governance, education, and online safety
- Enable research and innovation using Somali-language data
- Contribute to national capacity in AI and language technologies
Recent Updates
The project is progressing through phased development, including dataset preparation, prototype model development, and exploratory applications in areas such as text analysis and online content moderation.
Updates and research outputs will be published as tools and models reach deployment and evaluation stages.
How the Project Works
The project brings together Somali-language data and modern AI techniques to build foundational NLP capabilities. Language data are carefully curated, cleaned, and structured to ensure quality and representativeness.
AI models are then trained to recognize patterns in Somali text and speech, enabling applications such as text analysis, speech recognition, and automated content understanding. Outputs are designed to be practical, transparent, and adaptable for use in public-sector systems, research, and digital platforms.
Researchers and Collaborators
This project is implemented through collaboration between:
- Researchers from SIMAD University
- AI and data science experts affiliated with the SIMAD AI Institute
- National and international partners working on language technologies and digital inclusion
The collaboration brings together expertise in linguistics, AI, data science, and social computing to ensure technical quality and societal relevance.