Machine Translation System for the Industry Domain and Croatian Language

Author:

Dunđer Ivan1

Affiliation:

1. Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia

Abstract

Machine translation is increasingly becoming a hot research topic in information and communication sciences, computer science and computational linguistics, due to the fact that it enables communication and transferring of meaning across different languages. As the Croatian language can be considered low-resourced in terms of available services and technology, development of new domain-specific machine translation systems is important, especially due to raised interest and needs of industry, academia and everyday users. Machine translation is not perfect, but it is crucial to assure acceptable quality, which is purpose-dependent. In this research, different statistical machine translation systems were built – but one system utilized domain adaptation in particular, with the intention of boosting the output of machine translation. Afterwards, extensive evaluation has been performed – in form of applying several automatic quality metrics and human evaluation with focus on various aspects. Evaluation is done in order to assess the quality of specific machine-translated text.

Publisher

Faculty of Organisation and Informatics

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Methods of Improving Japanese-Chinese Machine Translation System through Machine Learning and Human-Computer Interaction;ACM Transactions on Asian and Low-Resource Language Information Processing;2023-08-19

2. Research on Machine Translation (MT) System Based on Deep Reinforcement Learning;2022 3rd International Conference on Computer Science and Management Technology (ICCSMT);2022-11

3. A Comparative Study of Text Genres in English-Chinese Translation Effects Based on Deep Learning LSTM;Computational and Mathematical Methods in Medicine;2022-06-02

4. Development of a mobile application for flag identification based on artificial neural networks;Zbornik Veleučilišta u Rijeci;2022

5. Named Entity Correction in Neural Machine Translation Using the Attention Alignment Map;Applied Sciences;2021-07-29

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