A model for constructing neural network systems forrecognizing emotions of text fragments

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Ihor A. Tereikovskyi
Oleksandr S. Korovii

Abstract

Emotion Recognition in text is a crucial task in Natural Language Processing, particularly relevant given the exponential growth of textual data from social media and voice interfaces. However, developing effective emotion recognition systems for low-resource languages, such as Ukrainian, faces significant challenges, including linguistic informality, dialectal variations, and cultural specificities. This paper introduces a modular model (framework) for developing neural network-based tools for recognizing emotions in Ukrainian text fragments. The model encompasses a comprehensive data preprocessing pipeline, flexible architectural choices (including approaches based on Word to Vector, Long Short-Term Memory, and Transformers), and rigorous validation using standard metrics and interpretability methods. As part of an experimental study, two prototypes were implemented and compared: a lightweight classifier based on FastText and a more powerful classifier based on pretrained RoBERTa-base, both trained to recognize seven basic emotions. The results demonstrate that RoBERTa-base achieves high accuracy, significantly outperforming FastText and a baseline translation-based approach, yet it demands substantially more computational resources for inference. The study underscores the importance of creating Ukrainian-language corpora to enhance recognition capabilities and highlights the critical trade-off between accuracy and efficiency. It provides practical recommendations for model selection based on resource constraints and performance requirements for emotion analysis tasks in the Ukrainian language.

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Theoretical aspects of computer science, programming and data analysis

Authors

Author Biographies

Ihor A. Tereikovskyi, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 37, Beresteiskyi Ave. Kyiv, 03056, Ukraine

Doctor of Engineering Sciences, Professor, Professor of System Programming and Specialized Computer Systems Department

Scopus Author ID: 57195940293

Oleksandr S. Korovii, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 37, Beresteiskyi Ave. Kyiv, 03056, Ukraine

PhD student

Scopus Author ID: 57644238900

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