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A Review of Automatic Pre-editing Approaches in Machine Translation
WANG Jun-song, MENG Ya-qi, WANG Ai-qing
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DOI:10.17265/2159-5836/2025.06.006
Northwestern Polytechnical University, Xi’an, China Northwestern Polytechnical University, Xi’an, China University of Liverpool, Liverpool, United Kingdom
With the development of machine translation technology, automatic pre-editing has attracted increasing research attention for its important role in improving translation quality and efficiency. This study utilizes UAM Corpus Tool 3.0 to annotate and categorize 99 key publications between 1992 and 2024, tracing the research paths and technological evolution of automatic pre-translation editing. The study finds that current approaches can be classified into four categories: controlled language-based approaches, text simplification approaches, interlingua-based approaches, and large language model-driven approaches. By critically examining their technical features and applicability in various contexts, this review aims to provide valuable insights to guide the future optimization and expansion of pre-translation editing systems.
automatic pre-editing, machine translation, controlled language, text simplification, large language models
Journal of Literature and Art Studies, June 2025, Vol. 15, No. 6, 483-489
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