--- license: mit base_model: none tags: - arabizi - transliteration - arabic-nlp - arabic-dialects pretty_name: ArabiziKit trained layer --- # ArabiziKit trained layer The learned layer of the ArabiziKit hybrid transliteration system (https://github.com/rb2625/arabizi-kit), which converts Arabizi — Arabic written in Latin letters and digits (2 for hamza/qaf, 3 for ayn, 7 for ha, 5 for kha) — into Arabic script. Three small, dependency-free components, all pure Python: | component | file | what it does | | --- | --- | --- | | word reading table | `model.json` | Arabizi word → observed Arabic renderings with frequencies (1,155 entries), article-aware alignment (`el etnein` → `الاثنين`) | | character trigram LM | `model.json` | Laplace-smoothed trigram over corpus references, reranking each word's candidates toward natural Arabic | | Naive Bayes dialect classifier | `egyptian.json`, `levantine.json`, `maghrebi.json` | word tokens + Arabizi code markers; supplies the dialect hint automatically (only for dialects whose conventions change the engine's readings) | ## Training Trained on the calibration set plus the pipeline train/dev splits (`rb2625/arabizi-kit-corpus`) and public dialect text. Held-out test and external sets are excluded from training. ## Usage ```bash pip install arabizikit arabizikit model train # rebuild the model from the corpus arabizikit "bach n9ra" --model # learned layer on one sentence arabizikit eval --data test.json --model # reproduce the paper's numbers ``` ## Results (exact@1 / hit@3 / CER, from the paper) | set | rules, no hint | rules, oracle hint | learned layer | | --- | --- | --- | --- | | pipeline dev | 0.021 / 0.021 / 0.291 | 0.021 / 0.021 / 0.291 | 0.354 / 0.542 / 0.097 | | pipeline test | 0.000 / 0.000 / 0.299 | 0.000 / 0.000 / 0.299 | 0.061 / 0.102 / 0.226 | | Egyptian (external) | 0.376 / 0.526 / 0.236 | 0.376 / 0.526 / 0.236 | 0.348 / 0.502 / 0.248 | | Levantine (external) | 0.296 / 0.429 / 0.076 | 0.296 / 0.429 / 0.076 | 0.270 / 0.360 / 0.096 | | Moroccan Darija (external) | 0.035 / 0.057 / 0.235 | 0.088 / 0.115 / 0.180 | 0.053 / 0.080 / 0.207 | ## Paper "ArabiziKit: An Open, Hybrid, Benchmark-Driven Arabizi to Arabic-Script Transliteration System" (arXiv, cs.CL).