Alignment and Bilingual Corpora in IT-Based Translation for English Language Teaching: A Systematic Literature Review

Refika Andriani; Fatma Setya Ningrum; Meutya Rizki Ramadhani; Aura Syalshabillah

doi:10.30998/3rg2hx57

Authors

Refika Andriani Author
Fatma Setya Ningrum Author
Meutya Rizki Ramadhani Lancang Kuning University Author
Aura Syalshabillah Author

DOI:

https://doi.org/10.30998/3rg2hx57

Keywords:

Bilingual Corpus, Information Technology-Based Translation, Natural Language Processing

Abstract

The increasing integration of information technology into translation studies has repositioned alignment and bilingual corpora as central resources for both linguistic analysis and English language teaching. Although extensive research has explored corpus-based translation and natural language processing, existing studies remain scattered across technical, pedagogical, and sociocultural perspectives. This systematic literature review addresses this fragmentation by synthesizing empirical evidence on alignment practices and bilingual corpus construction in IT-based translation. Guided by PRISMA procedures, twenty-two peer-reviewed journal articles published between 2020 and 2025 were retrieved from Scopus, Crossref, and Google Scholar and analyzed through thematic synthesis. The findings reveal a clear shift from manual and rule-based alignment toward semi-automated and hybrid models that integrate NLP techniques with human linguistic validation. While technological innovation has enhanced scalability, accuracy, and analytical efficiency, persistent challenges remain in domain adaptation, low-resource languages, and the interpretation of culturally embedded meaning. The review further demonstrates that bilingual corpora play a significant pedagogical role by supporting data-driven learning, learner autonomy, and critical language awareness in translation and English language teaching contexts. Beyond technical application, aligned corpora also function as sociocultural artifacts that reflect ideology, identity, and communicative purpose across languages. This study contributes an integrative framework that connects computational alignment, linguistic interpretation, and pedagogical application within a unified perspective. The findings highlight the importance of hybrid human–machine approaches for sustainable corpus development and suggest broader implications for translation education, ELT practice, and inclusive multilingual research in digitally mediated learning environments.

Downloads

Download data is not yet available.

References

Ar Rusyfa, I. Z., Datang, F. A., & Junaidi, J. (2025). Positioning in news translation regarding Hamas: A parallel corpus-based approach. JOLLT Journal of Languages and Language Teaching, 13(1), 60–73. https://doi.org/10.33394/jollt.v13i1.13445

Ardi, H., Ermanto, N., Juita, N., & Vy Rany. (2025). L1 interference in students’ translations: A corpus-based analysis of collocation errors and pedagogical implications. International Journal of Language Pedagogy, 5(1), 93–105. https://doi.org/10.24036/ijolp.v5i1.113

Ayu Setiawati, N. M., Rajeg, I. M., & Matradewi, N. K. W. (2021). The translation’s equivalence of the word “support” in the parallel corpus English–Indonesian. Alford Council of International English & Literature Journal (ACIELJ), 4(4), 1–10. https://www.acielj.com

Bawden, R., Chaumartin, F.-R., Dymetman, M., Marie, B., & Wisniewski, G. (2021). DiaBLa: A corpus of bilingual spontaneous written dialogues for machine translation. Computational Linguistics, 47(4), 771–806. https://doi.org/10.1162/coli_a_00416

Bullock, B. E., Gerfen, C., & Toribio, A. J. (2021). Exploring a loan translation and its consequences in an oral bilingual corpus. Languages, 6(3), 137. https://doi.org/10.3390/languages6030137

Chen, L.-C. (2023). An improved corpus-based NLP method for facilitating keyword extraction: An example of the COVID-19 vaccine hesitancy corpus. Sustainability, 15(4), 3402. https://doi.org/10.3390/su15043402

Chen, L.-C., Chang, K.-H., & Yang, S.-C. (2022). Integrating corpus-based and NLP approaches to extract terminology and domain-oriented information: An example of the US military corpus. Acta Scientiarum Technology, 44(1), e60486. https://doi.org/10.4025/actascitechnol.v44i1.60486

Dang, P. (2024). The extraction method used for the English-Chinese machine translation corpus is based on bilingual sentence pair coverage. Open Computer Science, 14, 20230107. https://doi.org/10.1515/comp-2023-0107

Endarto, I. T. (2020). A corpus-based lexical analysis of Indonesian English as a new variety. Indonesian Journal of Applied Linguistics, 10(1), 95–106. https://doi.org/10.17509/ijal.v10i1.24993

Espinosa-Anke, L., Palmer, G., Corcoran, P., Filimonov, M., Spasić, & Knight, D. (2021). English–Welsh cross-lingual embeddings. Applied Sciences, 11(14), 6541. https://doi.org/10.3390/app11146541 ‬‬‬‬‬‬‬‬‬

Fonseca, C., Guelpeli, M., & Netto, R. (2022). Representation of structured data of the text genre as a technique for automatic text processing. Texto Livre Linguagem e Tecnologia, 15, e35445. https://doi.org/10.35699/1983-3652.2022.35445

Giampieri, P. (2023). Is machine translation reliable in the legal field? A corpus-based critical comparative analysis for teaching purposes. Languages, 8(3), 194. https://doi.org/10.3390/languages8030194

Gorozhanov, A., Guseynova, I., & Степанова, Д. (2024). Natural language processing and fiction text: basis for corpus research. Rudn Journal of Language Studies Semiotics and Semantics, 15(1), 195–210. https://doi.org/10.22363/2313-2299-2024-15-1-195-210

Guo, Z. & Jifeng, Z. (2021). Japanese translation teaching corpus based on a bilingual non parallel data model. Journal of Intelligent & Fuzzy Systems, 40(2), 3731-3741. https://doi.org/10.3233/jifs-189407

Hu, L. and Hu, J. (2022). An exploration of the problems and solutions involved in translating computer software into Japanese. Mathematical Problems in Engineering, 2022, 1-9. https://doi.org/10.1155/2022/3712090

in, J., Tan, T., & Malancon, B. (2024). Hybrid distance-statistical-based phrase alignment for analyzing parallel texts in standard malay and malay dialects. Malaysian Journal of Computer Science, 37(1), 1-25. https://doi.org/10.22452/mjcs.vol37no1.1

Inácio, M., Cabezudo, M., Ramisch, R., Felippo, A., & Pardo, T. (2023). The amr-pt corpus and the semantic annotation of challenging sentences from journalistic and opinion texts. Delta Documentação De Estudos Em Lingüística Teórica E Aplicada, 39(3). https://doi.org/10.1590/1678-460x202339355159

Kwok, H. L., Laviosa, S., & Liu, K. (2023). Lexical simplification in learner translation: A corpus-based approach. Research in Corpus Linguistics, 11(2), 103–124. https://doi.org/10.32714/ricl.11.02.06

Leńko-Szymańska, A., & Biel, Ł. (2023). Terminological collocations in trainee and professional legal translations: A learner-corpus study of L2 company law translations. International Journal of Learner Corpus Research, 9(1), 29–60. https://doi.org/10.1075/ijlcr.22008.len

Li, Y. (2023). Key technologies for constructing bilingual corpus for english-chinese translation. The Frontiers of Society Science and Technology, 5(11). https://doi.org/10.25236/fsst.2023.051109

Li, Y. and Li, Z. (2023). Research on college english translation teaching based on parallel corpus. International Journal of New Developments in Education, 5(18). https://doi.org/10.25236/ijnde.2023.051818

Matvieieva, S. A. (2020). Translation of legal terms: Bilingual dictionary vs. parallel corpus. Science and Education a New Dimension: Philology, 8(67), 45–49. https://doi.org/10.31174/SEND-Ph2020-225VIII67-10

Pakaja, M., Pong, M., Som, R., & Sari, H. F. A. (2025). Development of an Indonesian–English parallel corpus for translation and comparative linguistics research. Journal International of Lingua and Technology (JILTECH), 4(1), 16–30. https://doi.org/10.55849/jiltech.v4i1.817

Quick, A. E., & Hartmann, S. (2021). The building blocks of child bilingual code-mixing: A cross-corpus traceback approach. Frontiers in Psychology, 12, 682838. https://doi.org/10.3389/fpsyg.2021.682838

Rajeg, I. M., & Rajeg, G. P. (2022). A corpus linguistic study of constructional equivalence for the Indonesian translation of ROB and STIMULUS-EXPERIENCER verbs in English. Linguistics and Literature Studies, 10(2), 33–48. https://doi.org/10.13189/lls.2022.100202

Saddhono, K., Rohmadi, M., Setiawan, B., Suhita, R., Rakhmawati, A., Hastuti, S., & Islahuddin, I. (2023). Corpus linguistics use in vocabulary teaching principle and technique application: A study of Indonesian language for foreign speakers. International Journal of Society, Culture & Language, 11(1), 232–245. https://doi.org/10.22034/ijscl.2022.1971972.2823

Shawaqfeh, A. T., & Khasawneh, M. A. S. (2023). Incorporating corpus linguistics tools in the training and professional development of lecturers in translation studies. Studies in Media and Communication, 11(7), 260–273. https://doi.org/10.11114/smc.v11i7.6379

Sianipar, I. F., & Sajarwa. (2022). The lexical equivalence variety of F-words translation into Indonesian: Corpus-based translation research. Lire Journal (Journal of Linguistics and Literature), 6(1), 53–70. https://doi.org/10.33019/lire.v6i1.140

Tan, T., Lim, C., & Rahman, W. (2021). Sliding window and parallel lstm with attention and cnn for sentence alignment on low-resource languages. Pertanika Journal of Science and Technology, 30(1), 97-121. https://doi.org/10.47836/pjst.30.1.06

Tian, C. (2023). The translation of culture-specific items (csis) in yellow river cultural corpus: a case study of history of the yellow river. English Language Teaching and Linguistics Studies, 5(3), p381. https://doi.org/10.22158/eltls.v5n3p381

Tran, P., Nguyen, T., Vu, D., Tran, H., & Vo, B. (2022). A method of chinese-vietnamese bilingual corpus construction for machine translation. Ieee Access, 10, 78928-78938. https://doi.org/10.1109/access.2022.3186978

Vanhaverbeke, M., Enghels, R., Couto, M., & Ivanova, I. (2025). Enhancing code-switching research through comparable corpora: introducing the el paso bilingual corpus. Languages, 10(7), 174. https://doi.org/10.3390/languages10070174

Vîlceanu, T. (2023). Integrating interview-based approaches into corpus-based translation studies and literary translation studies. Open Linguistics, 9, 20220265. https://doi.org/10.1515/opli-2022-0265

Xia, L. and Zhang, H. (2024). A study on the construction of a large-scale multimodal parallel corpus of typical official documents of China, 1(10), 72-76. https://doi.org/10.62381/p243a12

Xu, J. (2023). Translation studies from the perspective of corpus translation studies and digital humanities. Journal of Education, Teaching and Social Studies. https://doi.org/10.22158/jets.v5n4p45

Zhang, D. (2022). Research on process of the bilingual corpus alignment tool. Learning & Education, 10(5), 35. https://doi.org/10.18282/l-e.v10i5.2664

Zhang, L. (2022). Design of new word retrieval algorithm for Chinese–English bilingual parallel corpus. Mathematical Problems in Engineering. https://doi.org/10.1155/2022/4593129