SPECIALIZED NEURAL MACHINE TRANSLATION FOR AVIATION ENGLISH: INSIGHTS FROM PORTUGUESE-TO-ENGLISH AVIATION SAFETY REPORTS

Aviation safety reports are essential sources for the identification and analysis of risks in civil aviation. These reports are written in plain language, which requires the application of Natural Language Processing techniques for automatic and intelligent treatment. In the case of Brazil, the vast majority of reports are written in Portuguese. Therefore, for comparison with international database of reports that are written in English, a first step is the translation of Brazilian reports. In this work, a proposal for a machine translation model is presented based on the fine-tuning of pre-trained models. To this end, an aviation-specific language corpus is developed with the objective of generating example data for model training. Finally, a pre-trained model is fine-tuned with the corpus created in order to implement an automatic translation model that achieves good results in the task considering the specifics of the aviation language. As a result, a first model is implemented, presenting coherent results of translation between Portuguese/English in the specific domain of aviation.

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Publication Details

Journal
Revista Foco
Published
2024-09-02
DOI
https://doi.org/10.54751/revistafoco.v17n9-009
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

SPECIALIZED NEURAL MACHINE TRANSLATION FOR AVIATION ENGLISH: INSIGHTS FROM PORTUGUESE-TO-ENGLISH AVIATION SAFETY REPORTS

Ronaldo Wajnberg Gamermann, Fabio Junior Maneguello
Revista Foco
Natural Language Processing Techniques
article

SPECIALIZED NEURAL MACHINE TRANSLATION FOR AVIATION ENGLISH: INSIGHTS FROM PORTUGUESE-TO-ENGLISH AVIATION SAFETY REPORTS

Ronaldo Wajnberg Gamermann, Fabio Junior Maneguello
article en

Abstract

Aviation safety reports are essential sources for the identification and analysis of risks in civil aviation. These reports are written in plain language, which requires the application of Natural Language Processing techniques for automatic and intelligent treatment. In the case of Brazil, the vast majority of reports are written in Portuguese. Therefore, for comparison with international database of reports that are written in English, a first step is the translation of Brazilian reports. In this work, a proposal for a machine translation model is presented based on the fine-tuning of pre-trained models. To this end, an aviation-specific language corpus is developed with the objective of generating example data for model training. Finally, a pre-trained model is fine-tuned with the corpus created in order to implement an automatic translation model that achieves good results in the task considering the specifics of the aviation language. As a result, a first model is implemented, presenting coherent results of translation between Portuguese/English in the specific domain of aviation.

Revista FocoVol. 17(9)
Universidade Federal do Rio Grande do Sul (BR), Pontifícia Universidade Católica do Rio Grande do Sul (BR), Universidade Luterana do Brasil (BR)
Openalex Percentile: Top 88%
Natural Language Processing Techniques
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