Рақамли технологияларнинг назарий ва амалий масалалари Volume 7 Issue 3 (2024) · pp. 76-83
Development of a language model based on artificial neural networks for the uzbek language
Хужаяров, Илёс, Очилов, Маннон
Abstract
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.
Узбекский языкобработка естественного языкаязыковая модельнабор обучающих данныхглубокое обучениерекуррентные нейронные сетиоценка точности моделикоэффициент недоуменияUzbek languagenatural language processing
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