Today we’re diving into how artificial intelligence can help preserve and uplift languages that don’t have as many digital resources, such as Creoles, African dialects, and indigenous languages. If you care about language diversity and tech innovation, this one’s for you.
AI is transforming how we communicate and process language. But here’s the problem: most of this progress centers on high-resource languages like English or Mandarin. That means thousands of others risk being left behind.
The good news? The AI revolution can actually empower these languages, if we take the right steps.
First up—document and digitize!
AI models need large datasets, but many communities don’t have them yet. That’s where language professionals and native speakers come in.
Record stories, songs, conversations: anything that captures natural language use.
Projects like Masakhane in Africa and the MIT-Haiti Initiative for Haitian Creole show how communities can take ownership of this process.
The second tip: create bilingual or multilingual datasets.
Pairing lesser-resourced languages with high-resource ones like English or French helps AI systems learn faster.
You can join translation efforts through Duolingo, Wikipedia, or even volunteer projects from Translators Without Borders, which uses machine translation tools to support underserved languages.
Bonus Insight: You can also use AI tools to translate local literature and oral traditions into global languages. It’s a win-win—AI gets smarter, and your language reaches new audiences.
Many of these languages are primarily spoken, not written. So, speech recognition is key.
Use open-source projects like Mozilla’s Common Voice to collect and share audio samples.
And here’s a pro idea: develop a termbase, like Canada’s Termium for French, and link it with text-to-speech tools. That way, AI can pronounce and understand the language more naturally.
AI-friendly language policies make all the difference. Governments and organizations should fund research and promote open access to language data.
For example, South Africa is already supporting projects for Zulu and Xhosa language tools.
Call to Action: If you’re a linguist or researcher, advocate for funding and inclusion in your region!
Don’t wait for tech giants to notice your language. Reach out to AI researchers and partner up.
Projects like Masakhane are built on volunteer collaboration between linguists and data scientists. That’s the model we need: community-led AI.
AI can help build dictionaries, unify spelling variations, and even suggest new words.
In Haiti, AI-driven lexicon expansion is enriching Haitian Creole resources, part of a broader movement through the Caribbean Digital Library.
From ancient manuscripts to oral storytelling, AI can help preserve it all.
Use tools like OCR to digitize old texts, and AI translators to share them globally. Google’s translation models are already helping expand Yoruba and Igbo content.
Community engagement is essential. Train locals in data collection, transcription, and ethical AI use. Always get consent and respect cultural traditions.
Open-source tools democratize access.
Contribute your data or models to platforms like Hugging Face, GitHub, or OpenNLP.
It’s not just about one language—it’s about creating a culture of linguistic inclusion.
We need more language technologists from within these communities.
Support scholarships, start AI courses, or partner with initiatives like the African Language Technology Initiative (ALT-I) and Howard University’s African Languages Translation Initiative.
AI is not the enemy. It’s a tool for empowerment. If we document, collaborate, and innovate together, every language, from Haitian Creole to Yoruba, can thrive in the digital age.
Preserve. Empower. Share.
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