Automated Evaluation Metric for Terminology Consistency in MT
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457089" target="_blank" >RIV/00216208:11320/22:10457089 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Automated Evaluation Metric for Terminology Consistency in MT
Popis výsledku v původním jazyce
The most widely used metrics for machine translation tackle sentence-level evaluation. However, at least for professional domains such as legal texts, it is crucial to measure the consistency of the translation of the terms throughout the whole text. This paper introduces an automated metric for the term consistency evaluation in machine translation (MT). To demonstrate the metric's performance, we used the Czech-to-English translated texts from the ELITR 2021 agreement corpus and the outputs of the MT systems that took part in WMT21 News Task. We show different modes of our evaluation algorithm and try to interpret the differences in the ranking of the translation systems based on sentence-level metrics and our approach. We also demonstrate that the proposed metric scores significantly differ from the widespread automated metric scores, and correlate with the human assessment.
Název v anglickém jazyce
Automated Evaluation Metric for Terminology Consistency in MT
Popis výsledku anglicky
The most widely used metrics for machine translation tackle sentence-level evaluation. However, at least for professional domains such as legal texts, it is crucial to measure the consistency of the translation of the terms throughout the whole text. This paper introduces an automated metric for the term consistency evaluation in machine translation (MT). To demonstrate the metric's performance, we used the Czech-to-English translated texts from the ELITR 2021 agreement corpus and the outputs of the MT systems that took part in WMT21 News Task. We show different modes of our evaluation algorithm and try to interpret the differences in the ranking of the translation systems based on sentence-level metrics and our approach. We also demonstrate that the proposed metric scores significantly differ from the widespread automated metric scores, and correlate with the human assessment.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/GX20-16819X" target="_blank" >GX20-16819X: Porozumění jazyku: od syntaxe k diskurzu</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů