Development of a language model based on artificial neural networks for the uzbek language

Хужаяров, Илёс, Очилов, Маннон

Рақамли технологияларнинг назарий ва амалий масалалари · 2024-yil

Annotatsiya

This research work aims to develop a model of the Uzbek language using artificial neural networks to improve natural language processing (NLP) capabilities. The article classifies various methods of creating language models and presents the stages of designing a language model using architectures such as recurrent neural networks (RNN) and long short-term memory (LSTM) networks. It also discusses the evaluation index for neural language models. Additionally, the text base features used to create the language model, the proposed neural network architecture, the hyperparameters of the neural network, and the obtained results are highlighted.

Maqola ma’lumotlari
MualliflarХужаяров, Илёс, Очилов, Маннон
JurnalРақамли технологияларнинг назарий ва амалий масалалари
Nashr sanasi2024-10-09
Jild7
Son3
Betlar76-83
TilRus
DOI10.62132/ijdt.v7i3.199

Kalit so‘zlar

Узбекский язык, обработка естественного языка, языковая модель, набор обучающих данных, глубокое обучение, рекуррентные нейронные сети, оценка точности модели, коэффициент недоумения, Uzbek language, natural language processing, language model, training dataset, deep learning, recurrent neural networks, model accuracy assessment, perplexity coefficient

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