mlsanityData to 7 Oct 2026

Bridging the Usability Gap: Lessons from Interpreting Studies for Machine Interpreting Design

arXiv 2606.16009 ↗First posted 14 Jun 2026cs.CL cs.HCcited by 0

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Abstract (arXiv)

Machine interpreting (MI), the live, real-time application of speech translation, has achieved remarkable progress on standard benchmarks, with some systems approaching human parity on textual fidelity. Yet the user experience remains far inferior to interpreter-mediated communication, revealing what we term the accuracy illusion: systems that appear accurate on paper but fail in practice to support smooth, goal-oriented interaction. This paper defines MI as a distinct subfield of speech translation, with its own characteristics and the need for evaluation methods grounded in communicative effectiveness rather than isolated fidelity metrics. Drawing on insights from interpreting studies, we identify critical dimensions of professional interpreting practice that are overlooked by current systems, and consolidate them into three interdependent design priorities for future MI: agency (context-sensitive initiative and repair), grounding (multimodal and discourse-level situational awareness), and experience (adaptive improvement through real interaction). Together, these priorities chart a path toward closing the usability gap and enabling systems that can sustain authentic multilingual communication in real time.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 21 of its 59 references that are in the map. First posted on arXiv 14 Jun 2026.

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References · 21

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9 more
  1. 2021Neural Dubber: Dubbing for Videos According to Scriptscited by 39
  2. 2017Bandit Structured Prediction for Neural Sequence-to-Sequence Learningcited by 31
  3. 2024How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?cited by 17
  4. 2024Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agentcited by 14
  5. 2022MT Metrics Correlate with Human Ratings of Simultaneous Speech Translationcited by 9
  6. 2021Towards the evaluation of automatic simultaneous speech translation from a communicative perspectivecited by 8
  7. 2025Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactionscited by 8
  8. 2023Direct Models for Simultaneous Translation and Automatic Subtitling: FBK@IWSLT2023cited by 6
  9. 2024Exploring the Correlation between Human and Machine Evaluation of Simultaneous Speech Translationcited by 4

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