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Rubric-Aligned Disentangled Evaluation of Human Simultaneous Interpreting

arxiv.org/abs/2609.11131

quality89

Updated 7 h ago · first seen 11 Sept 2026

paper_01M294G4HQP9BV3Q026Q9EHFWP

Published
11 Sept 2026
T1 · 7 h ago
arXiv
2609.11131
T1 · 7 h ago
Category
cs.CL
T1 · 7 h ago

Abstract

Human simultaneous interpreting (SI) is commonly assessed with analytic rubrics separating meaning transfer, delivery quality, and temporal synchrony, yet no automatic metric is designed for rubric-aligned segment-level SI evaluation. We construct a professionally annotated corpus of 1,101 SI segments with scores for meaning transfer (LQ), delivery quality (EXP), and perceived latency (LAT). We show that structured LLM prompting and scalar supervision collapse rubric dimensions, yielding near-zero correlation with human ratings and strong cross-dimension coupling. To isolate supervision structure under identical backbone capacity, we introduce dual regression heads on a LoRA-adapted COMET-KIWI encoder. On a held-out talk-level test set, the model achieves Pearson correlations of 0.388 (LQ) and 0.301 (EXP), improving over frozen COMET-KIWI. Given low absolute rater agreement, we interpret results relative to human consistency and target stable ranking signals for formative assessment.

Authors 2

Ziyu Zhang, Satoshi Nakamura

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

Arxiv announce type
new

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

arXiv id
2609.11131

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

Categories
cs.CL

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

Primary category
cs.CL

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

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Attributed facts

9

Source tiers

T19

Freshest observation

7 h ago

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None