O‘ZBEK TILIDAGI SHEVALARNI GAP DARAJASIDA ANIQLASHDA MASHINALI O‘QITISH ALGORITMLARINING QIYOSIY TAHLILI
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Ushbu tadqiqotda o‘zbek tili shevalarini avtomatik tasniflash vazifasi ko‘rib chiqiladi. Tabiiy tilni qayta ishlash (NLP) sohasida hozirda o‘zbek tili uchun resurslar kundan-kunga rivojlanib bormoqda va bu o‘z navbatida dialektologik korpuslarning yetishmasligi kabi muammolarni yuzaga keltiradi. Mazkur ishda kichik hajmdagi, turli shevalardan iborat ma’lumotlar to‘plami “Bag-of-Words” usuli bo‘lgan TF-IDF + Naive Bayes va bert-base-multilingual-cased modeli asosida tekshirildi. Tadqiqotning asosiy xulosasi, o‘zbek dialektologiyasida yuqori aniqlikdagi model qurilishidagi asosiy muammo bu faqatgina algoritm emas, balki yuqori sifatli, keng qamrovli annotatsiya qilingan korpusning yo‘qligidir.
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