Multimodal Language Testing for Interpreter Training Designing and Implementing an AI-Supported Proficiency Test for Punjabi Public Service Interpreters in Greece

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Published: Dec 28, 2025
DOI: https://doi.org/10.12681/ijltic.43367
Keywords:
language proficiency migration and asylum multimodal assessment Public Service Interpreting Punjabi AI-supported language testing
Effrossyni Fragkou
a:1:{s:5:"en_US";s:46:"National and Kapodistrian University of Athens";}
Abstract

This article documents the design and implementation of Greece’s first multimodal, AI-supported proficiency test for Punjabi public service interpreters, developed in response to the March 2024 launch of the Public Service Interpreter Register. The test addresses the complex sociolinguistic and logistical realities faced in the Greek asylum and migration context. The paper reviews current frameworks for interpreter competence and language proficiency—drawing on Common European Framework of Reference (CEFR) standards—and critiques the limitations of traditional assessment models. The Punjabi test integrates audio-based tasks and visual cues, leveraging AI-generated prompts to accommodate dialectal and literacy variation, prioritizing fairness and scalability, thus offering a replicable model for rare and minority languages where written resources, local expertise, and institutional infrastructure are lacking. The paper concludes by evaluating initial implementation outcomes, highlighting both the potential and limitations of multimodal and AI-assisted testing approaches in professionalizing public service interpreting and safeguarding the communicative rights of vulnerable populations.

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