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Researchers from the University of Maryland and the Association for Computational Linguistics have developed a framework for measuring how users form mental models of speech translation systems. The study identifies that users rely heavily on perceived translation incompleteness and phonetic noise to determine the reliability of AI-generated translations and the necessity for human intervention.