An Intelligent Proofreading System for Computer-Assisted English Translation Using a Fuzzy Decision Algorithm

• Xueqin Li,

Vol. 20, No. 1, January 31, 2026
10.3837/tiis.2026.01.001, Download Paper (Free):

• Attribute differentiation
• context analysis
• English translation
• fuzzy decision
• proofreading

Abstract

A computer-assisted English translation is optimal for proofreading documents, texts, etc., for reducing grammatical and sentence formation errors. In a computer-assisted translation process, the machine learns the representation of the words, texts, and sentences for error-less outcomes. This article introduces a Contextual Proofreading for Error Reduction (CPER) method to identify trivial errors due to multi-attribute-based sentence formation. The proposed method identifies translation errors due to the multi-attributes of the words and the formation of sentences. The provided sentence is validated using multiple-word swapping and rearrangement to determine the least error representation. In this error detection, the maximum probabilities of swapping and attribute changes are performed using a fuzzy decision algorithm. The CPER approach uses a fuzzy decision algorithm to evaluate and verify phrases by rearranging and swapping words and choosing configurations with the lowest mistake rate. Ensuring high accuracy, the system filters and refines these setups using context analysis. The fuzzy choice technique permits constant and accurate proofreading by repeatedly avoiding translations with high probability mistakes. This process is converged using maximum to minimum fuzzy decisions filtered from the previous context analysis. Therefore, this method improves error-free proofreading for different-sized English translation documents/ texts. The suggested CPER approach guarantees error-free proofreading for papers of various lengths. Translation accuracy enhanced by 11.82% compared to standard methods, and mistakes dropped by 11.46%.

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