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On Building a Bilingual Terminology Corpus from the Perspective of Human-machine Collaborative Translation

Guardado en:
Udgivet i:The Educational Review, USA vol. 9, no. 7 (2025), p. 658-664
Hovedforfatter: Wei, Jiameng
Andre forfattere: Li, Yi
Udgivet:
Hill Publishing Group Inc
Fag:
China
Teaching
Students
Collaboration
Curricula
Higher education
Service industries
Academic discourse
Social sciences
Editing
Phonetics
Educational attainment
Translation instruction
Language
Accuracy
Machine translation
Chinese history
Artificial intelligence
Technology education
Terminology
Bilingualism
Language modeling
Scholarly communication
Databases
Models
Humanities
Innovations
Translation
Extraction
Technical skills
Academic writing
Literature Reviews
Phonetic Transcription
Glossaries
Professional Education
Database Management Systems
Engines
Group Unity
Competence
Proofreading
Instructional Innovation
Educational Resources
Influence of Technology
Curriculum Design
Database Design
Educational Technology
Service Occupations
Teaching Models
Data Analysis
Educational Trends
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Resumen:The rapid advancements in artificial intelligence and large language models have significantly improved the quality of machine translation, profoundly influencing not only professional translation workflows but also driving pedagogical innovation in translation teaching at the higher education level. However, the ongoing issue of terminological and conceptual inaccuracies in current machine translation systems highlights the need for further refinement. Given the centrality of terminology in academic discourse, ensuring accuracy in terminological translation is essential for facilitating effective scholarly communication. This paper seeks to propose a methodological framework for the systematic extraction of bilingual terminological data to support the development of specialized corpora, with a particular focus on the social sciences and humanities. The primary aim is to maintain terminological precision and conceptual consistency while ensuring strong contextual alignment. Additionally, the paper aims to design an innovative teaching model to equip translation students with the technical skills required to create discipline-specific bilingual terminology databases, addressing a critical competency gap in the contemporary language services industry.
ISSN:2575-7938
2575-7946
DOI:10.26855/er.2025.07.005
Fuente:Education Database