面向航空手册的偏向性检索增强集成翻译模型

doi:10.11896/jsjkx.241100022

Abstract

Abstract: The aviation manuals refer to publications related to the design of large civil aircrafts,including flight manuals,maintenance manuals,and safety manuals.As a type of technical documentation that demands a high level of clarity and precision in language expression,the translation of aviation manuals requires adherence to the Simplified Technical English Specification(STE).STE is a controlled natural language that imposes explicit and stringent rules on the use of grammar and vocabulary in documentation.This paper proposes a biased retrieval-augmented ensembling translation model(BRAETM) for aviation manuals guided by STE.Within the model,biased target language sequences with the same sentence type and with lengths that meet the specification are cross-lingually retrieved to guide the translation generation at the decoder end,and a biased decoding strategy guided by the STE dictionary is adopted to correct the words in the translation.Outside the model,a non-passive translation model is selectively ensembled according to the estimation results of a prediction module,in order to generate more standardized translations in terms of sentence structure,voice and vocabulary.Experimental results show that the proposed model can generate translations that better adhere to the STE rules.Compared to the state-of-the-art baseline models,the BLEU scores of this model on two aviation manual test corpora are improved by 3.60 and 2.67,respectively.

Key words: Neural machine translation, Simplified technical English, Biased translation memory, STE Dictionary

CLC Number:

TP391

YANG Chen, YE Na, ZHANG Guiping. Biased Retrieval-augmented Ensembling Translation Model for Aviation Manuals[J].Computer Science, 2025, 52(11A): 241100022-10.

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Biased Retrieval-augmented Ensembling Translation Model for Aviation Manuals

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