Backtranslation Feedback Improves User Confidence in MT, Not Quality

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10440592" target="_blank" >RIV/00216208:11320/21:10440592 - isvavai.cz</a>

Výsledek na webu

<a href="https://aclanthology.org/2021.naacl-main.14/" target="_blank" >https://aclanthology.org/2021.naacl-main.14/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/2021.naacl-main.14" target="_blank" >10.18653/v1/2021.naacl-main.14</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Backtranslation Feedback Improves User Confidence in MT, Not Quality

Popis výsledku v původním jazyce

Translating text into a language unknown to the text&apos;s author, dubbed outbound translation, is a modern need for which the user experience has significant room for improvement, beyond the basic machine translation facility. We demonstrate this by showing three ways in which user confidence in the outbound translation, as well as its overall final quality, can be affected: backward translation, quality estimation (with alignment) and source paraphrasing. In this paper, we describe an experiment on outbound translation from English to Czech and Estonian. We examine the effects of each proposed feedback module and further focus on how the quality of machine translation systems influence these findings and the user perception of success. We show that backward translation feedback has a mixed effect on the whole process: it increases user confidence in the produced translation, but not the objective quality.

Název v anglickém jazyce

Backtranslation Feedback Improves User Confidence in MT, Not Quality

Popis výsledku anglicky

Translating text into a language unknown to the text&apos;s author, dubbed outbound translation, is a modern need for which the user experience has significant room for improvement, beyond the basic machine translation facility. We demonstrate this by showing three ways in which user confidence in the outbound translation, as well as its overall final quality, can be affected: backward translation, quality estimation (with alignment) and source paraphrasing. In this paper, we describe an experiment on outbound translation from English to Czech and Estonian. We examine the effects of each proposed feedback module and further focus on how the quality of machine translation systems influence these findings and the user perception of success. We show that backward translation feedback has a mixed effect on the whole process: it increases user confidence in the produced translation, but not the objective quality.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GX19-26934X" target="_blank" >GX19-26934X: Neuronové reprezentace v multimodálním a mnohojazyčném modelování</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

ISBN

978-1-954085-46-6

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

151-161

Název nakladatele

Association for Computational Linguistics

Místo vydání

Stroudsburg, PA, USA

Místo konání akce

Online

Datum konání akce

6. 6. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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