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Exploring Google Translate-friendly strategies to optimize Google Translate quality in the context of academic writing

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Doi: 10.1007/s43545-022-00455-z. Epub 1 August 2022.

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Affiliation 1 Institute for Teaching English to Speakers of Other Languages, National Yang Ming Jiaotong University, 1001 University Road, Hsinchu, 300 Taiwan.

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Yu-Chih Sun et al. SN Soc Sci. 2022.

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Doi: 10.1007/s43545-022-00455-z. Epub 2022 Aug 1. Affiliation 1 Institute of Teaching English to Speakers of Other Languages, National Yang Ming Chiao Tung University, 1001 University Rd., Hsin-chu, 300 Taiwan.

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Overview

In this study, we investigated the types of errors found in Google Translate (GT) Chinese to English translations, and based on those error types, we proposed strategies for optimizing the performance of GT. . From his seven articles published in English Teaching and Learning in 2017, his seven abstracts written in both Chinese and English were selected as materials. The researchers compared the GT translations with the English abstracts written by the original authors to analyze translation problems. Problematic translations consisted of grammatical errors (35%) and lexical errors (65%). In this context, we propose his nine specific strategies for use in preparing Chinese abstracts to be translated into English using GT. According to the strategy, users should (1) avoid expressions specific to their native language, (2) maintain the use of original English terminology when creating Chinese abstracts, and (3) discipline-specific discourse communities. We propose to reinforce logical relationships and expressions for Further analysis revealed that 99% of the 69 problems identified in the GT translations of the seven abstracts could be avoided using the proposed strategy. A conceptual framework for collaboration between GT and GT users is proposed and its educational implications are discussed.

Keywords: Academic Writing. English for Academic Purposes; Google Translate; Machine Translation.

The author retains exclusive rights to this article under an exclusive license to Springer Nature Switzerland AG 2022 by Springer Nature or its licensors under a publishing agreement with the author or other rights holder. The author’s self-archiving of the accepted manuscript version of this article is governed solely by the terms of such publication agreement and applicable law.

Conflict of Interest Statement

Conflict of interest On behalf of all authors, the corresponding author declares that there are no conflicts of interest.

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conceptual framework for cooperation between

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A conceptual framework for how users work with Google Translate

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A conceptual framework for how users work with Google Translate

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References Alhaisoni E, Alhaysony M. A survey of Saudi Arabian EFL college students’ attitudes towards the use of Google Translate. Int J Engl Lang Educ.2017;5(1):7282.Doi:10.5296/ijele.v5i1.10696.-DOI Chandra SO, Yuyun I. Using his Google Translate in EFL essay writing. LLT J. 2018;21(2):228238. Doi: 10.24071/llt.v21i2.1539. – DOI Chon YV, Shin D. Handwriting, translation writing, and machine translation writing: text-level analysis using Coh-Metrix. I will teach you English. 2020;75(1):2548. DOI: 10.15858/engtea.75.1.202003.25. – DOI United Nations Department of Economic and Social Affairs (23 February 2022) Goal 17: History. https://sdgs.un.org/goals Duker C, Shoquette DH. Machine Translation and the L2 Classroom: An Educational Solution to Reconcile with Google Translate. Foreign Langguan. 2018;51(4):779795. Doi: 10.1111/flan.12366.-Doi

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