"#Tigrinya and the rest of African languages, and by extension the hundreds of millions of people that speak these languages, are an afterthought for them."

"When you compare #NLLB systems for African languages against those supported by Lesan (https://lesan.ai) or Ghana NLP (https://ghananlp.org), their systems have lower quality and are generally sub-optimal."

https://ghananlp.org

These letter frequency heatmaps for #Amharic and #Tigrinya are derived from #Unicode's Unilex project (https://github.com/unicode-org/unilex). While the data is in need of some refinement, the heatmaps give a sense of priority for glyph creation: