The interpreter as developer: An autoethnographic design study of building a computer-assisted interpreting tool through human-LLM co-creation

Abstract:Real-time AI captioning now serves audiences at multilingual events, yet computer-assisted interpreting (CAI) tools are still built for interpreters, rarely by them. This article reports an autoethnographic design study in which a professional interpreter with no programming training built a local-first CAI system through expert-led 'vibe coding', co-creating with an LLM architect and a coding agent. Analysis of the complete development dialogues shows how tacit professional knowledge, from segmentation to booth infrastructure, was externalized into design after generic defaults failed in use. In a demanding public scientific event, three mechanisms of in-booth appropriation emerge under a firmly human-led division of labor; telemetry from a first fully instrumented assignment shows a fully local chain sustaining a median translation latency of 0.94 s across 971 utterances. The case is read as lead-user innovation newly enabled by generative AI, with implications for the technological literacy of interpreters and the future of interpreter training.

14 pages, 2 figures. The CAI tool is openly available at this https URL and archived at Zenodo, DOI https://doi.org/10.5281/zenodo.22255011

Computation and Language (cs.CL)

arXiv:2610.16460 [cs.CL]

(or arXiv:2610.16460v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2610.16460 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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