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Hybrid Deep Model for Uzbek Language Punctuation Prediction | Synapse

March 25, 2026Open Access

Hybrid Deep Model for Uzbek Language Punctuation Prediction

Key Points

The aim is to enhance automatic punctuation restoration for the Uzbek language using deep learning.
Developed a hybrid deep learning model.
Applied the model to a low-resource language, Uzbek.
Utilized existing annotated corpora for training.
Improved punctuation accuracy compared to previous methods.
Demonstrated effectiveness in low-resource language applications.

Abstract

Automatic punctuation restoration is one of the important tasks in natural language processing, especially for low-resource languages such as Uzbek, where this problem remains particularly relevant. The lack of sufficiently annotated corpora negatively affects the performance of downstream applications, including sp

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Cite This Study

Sharipov et al. (Sat,) studied this question.

synapsesocial.com/papers/69c37afeb34aaaeb1a67d0b8 https://doi.org/https://doi.org/10.29013/esr-26-1.2-41-46