Zamonaviy dunyoda innovatsion tadqiqotlar 4-jild vative-son (2025) · 111–113-betlar

EXPLAINABLE AI FOR TRANSLATOR TRUST

Abduganiyeva, Djamila

DOI: 10.5281/zenodo.17150308 · Manbada o'qish →

Annotatsiya

This paper explores how explainable-AI (XAI) techniques – visual attention maps, feature-attribution graphs and confidence heat-lines – can be operationalised in real-time dashboards that let professional translators audit the reasoning of neural-machine-translation (NMT) engines. Building on recent work in MT interpretability and user-centred design, we synthesise design principles (granular salience, cognitive frugality, cross-modal alignment, and low-resource adaptability) and analyse three case studies – Translation Canvas, NMT Visualising Tools and an open-source XAI toolkit – demonstrating their impact on trust and revision effort. We also consider the Uzbek MT ecosystem, showing how locally authored corpora and Turkic-language initiatives expand XAI research. Recommendations are offered for future hybrid human-AI workflows.

explainable AI; machine translation; translator trust; dashboard design; interpretability; neural MT; low-resource languages; Turkic linguistics

Metadata manbasi: jurnal OAI-PMH arxivi · Sindex to'liq matnni saqlamaydi, manbaga havola beradi.