A DIGITAL HUMANITIES APPROACH: PRACTICAL INSIGHTS INTO TRANSLATION STUDIES IN THE AI ERA
A DIGITAL HUMANITIES APPROACH: PRACTICAL INSIGHTS INTO TRANSLATION STUDIES IN THE AI ERA

Summary/Abstract: Translation Studies in the AI era are undergoing a profound transformation, yet a significant pedagogical gap persists: the disconnect between rapid computational advancement and the availability of accessible, reproducible training methodologies for instructors. The integration of AI, machine learning, and digital tools has reshaped traditional paradigms, prompting scholars to rethink the boundaries of translation studies today. This article addresses this challenge by establishing an integrative framework for “Applied Digital Humanities” within translation pedagogy. We propose and document two open-source computational solutions: a Python-based audio processor for MP3 segmentation and a customized “Consecutive Translation Trainer” designed to automate material preparation and enable the creation of CEFR-aligned, differentiated training corpora. The practical report suggests that Digital Humanities emerges as a powerful framework that bridges computational methods with humanistic inquiry. The integration of artificial intelligence into digital humanities has profoundly transformed the field of translation studies, where the practical applications of AI technologies such as automated MP3 splitting, text-to-speech systems, AI assistants for code verification, and corpus-based approaches are highly valued. These technologies contribute to more efficient workflows, enhance linguistic research, and expand the methodological toolkit available to translation scholars. Our custom tools, the Google Colab-based Anokhina_mp3splitter.ipynb and the desktop ‘Consecutive Translation Trainer’, are documented in the practical report and the article, respectively. By situating these applications within the broader context of digital humanities, the practical report demonstrates how AI tools both expand scholarly opportunities and introduce new challenges, particularly in areas of code optimization and error management. The translation studies in the AI era must adopt an interdisciplinary approach, merging computational expertise with linguistic skills. Our research demonstrates that these tools improve pedagogical efficiency, ensure material uniformity, and overcome the limitations of manual material creation.

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