KATTA HAJMLI MA’LUMOTLARDAN OVOZLI XABARLARNI AJRATIB OLISHDA PARALLEL HISOBLASH ALGORITMLARI VA UNING DASTURIY MAJMUASINI ISHLAB CHIQISH
DOI:
https://doi.org/10.5281/zenodo.17439211Keywords:
Parallel hisoblash, katta hajmli ma’lumotlar, ovozli xabarlarni ajratib olish, MapReduce, CUDA, Big Data, algoritm, dasturiy majmuaAbstract
Ushbu maqolada katta hajmli ma’lumotlardan ovozli xabarlarni ajratib olish masalasi ko‘rib chiqiladi. So‘nggi
yillarda raqamli ma’lumotlar hajmining keskin ortishi natijasida an’anaviy ketma-ket hisoblash usullari samaradorligini
yo‘qotmoqda. Shu sababli, maqolada parallel hisoblash texnologiyalariga asoslangan yondashuv taklif etiladi. Taklif
etilgan algoritm ovozli ma’lumotlar oqimini tezkor qayta ishlash, shovqindan tozalash va nutq segmentlarini ajratib olish
imkonini beradi. Bunda MapReduce, CUDA va Dask kabi parallel hisoblash modellaridan foydalanilgan. Mazkur tadqiqot
sun’iy intellekt, nutqni aniqlash, media ma’lumotlarni qayta ishlash hamda Big Data tizimlarida qo‘llash uchun amaliy
ahamiyatga ega.
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