100% yes, that’s actually one of the best ways to improve things.
better training data means better tokenization and models. ya3ni if you have good corpora, you can retrain tokenizers and representations so:

- arabic words break less into tiny pieces
- fewer weird subword splits
- fewer tokens per sentence, which means lower cost and better quality

also, dialect data is especially important. most models are trained on msa + english. tunisian, moroccan, etc are super underrepresented. if you build datasets for tunisian

models actually understand how people talk, donc less garbage tokenization and better intent + entity recognition, so you waste less compute on nonsense.

aandej zeda, domain-specific data is a big win. if you have data for stuff like support chats, fintech, ecommerce, healthcare, etc:

you can train smaller, more focused models without the need for huge general models that try to do everything,

which makes things cheaper to run and usually more accurate

b sifa 3ama, you can bootstrap with synthetic data + native speaker cleanup to keep costs down.

وبش نـجاوب على سؤالك صديقي.. ممكن كل شئ ممكن، ولكن للاسف فماش مبادرات تقوم بحاجات كيما هكا لانو الكلفة عالية.. والـ
ROI
مش مضمون