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A Probe into the Design of 3 Computer Aided English Translation Teaching in the Era of Big Data

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DOI: 10.23977/curtm.2022.051006 | Downloads: 7 | Views: 476

Author(s)

Ruijie Gao 1

Affiliation(s)

1 School of Marxism, Sichuan Water Conservancy Vocational and Technical College, Chengdu, Sichuan, China

Corresponding Author

Ruijie Gao

ABSTRACT

Confronted with the problems of low quality and efficiency of manual translation within high cost in current scientific and technical English, A computer-assisted English translation system based on the auxiliary translation software--Trados is designed. With the purpose of improving translation efficiency and quality, while reducing translation costs, the system function modules are constituted by three modules--translation memory, translation retrieval module, and translation editing environment. Firstly, a translation memory model is established, and the input English is accurately searched and verified through the translation memory library, and then the translation retrieval module is used to match the corpus with higher similarity, specifically by using the "shortest edit distance" method to verify the corpus Perform evaluation calculations and classify corpora with a higher degree of similarity. After preliminary matching in the translation editing environment, a more realistic and accurate English corpus translation can be realized. Finally, the translation results are tested. The test results reveal that the Trados-based computer-assisted English translation system proposed in this study has high translation accuracy and professionalism, which can greatly improve the quality and efficiency of translation. This study is characterized by practical meaning for the development of translation teaching and research field.

KEYWORDS

Trados software, computer-aided translation, translation memory, similarity matching

CITE THIS PAPER

Ruijie Gao, A Probe into the Design of 3 Computer Aided English Translation Teaching in the Era of Big Data. Curriculum and Teaching Methodology (2022) Vol. 5: 34-40. DOI: http://dx.doi.org/10.23977/curtm.2022.051006.

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