Average Token Delay: A Duration-aware Latency Metric for Simultaneous Translation

November 24, 2023 ยท Declared Dead ยท ๐Ÿ› Journal of Natural Language Processing

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Authors Yasumasa Kano, Katsuhito Sudoh, Satoshi Nakamura arXiv ID 2311.14353 Category cs.CL: Computation & Language Citations 3 Venue Journal of Natural Language Processing Last Checked 5 months ago
Abstract
Simultaneous translation is a task in which the translation begins before the end of an input speech segment. Its evaluation should be conducted based on latency in addition to quality, and for users, the smallest possible amount of latency is preferable. Most existing metrics measure latency based on the start timings of partial translations and ignore their duration. This means such metrics do not penalize the latency caused by long translation output, which delays the comprehension of users and subsequent translations. In this work, we propose a novel latency evaluation metric for simultaneous translation called \emph{Average Token Delay} (ATD) that focuses on the duration of partial translations. We demonstrate its effectiveness through analyses simulating user-side latency based on Ear-Voice Span (EVS). In our experiment, ATD had the highest correlation with EVS among baseline latency metrics under most conditions.
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