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ACCOLÉ: A Collaborative Platform of Error Annotation for Aligned Corpora

By Emmanuelle Esperança-Rodier, Francis Brunet-Manquat and Sophia Eady

Abstract

International audienceThis article presents a platform, named ACCOLÉ, for the collaborative annotation of translation errors. ACCOLÉ offers a range of services that allow simplified management of corpora and error typologies, annotation of effective errors, collaborative discussion during annotation, and finally different kinds of search in corpora. ACCOLÉ allows the annotation of translation errors according to built-in error typologies, Vilar's typology or DQF-MQM or uploaded ones, on several annotated corpora of different texts, translated by different Statistical or Neural MT systems. It also help to process the annotated corpora created in order to look for typical error models and patterns, related to a specific MT system. ACCOLÉ currently provides 15 corpora, 19 projects of 134,273 source words and 114,511 target words, and 23,525 annotations. Eventually, we will implement the semi-automatic propagation of found patterns on other corpora to compare the behaviour of the MT systems on different domains, thus providing to the community a wide range of error-annotated bilingual parallel corpora

Topics: [SCCO.LING]Cognitive science/Linguistics, [SCCO.COMP]Cognitive science/Computer science
Publisher: HAL CCSD
Year: 2019
OAI identifier: oai:HAL:hal-02363208v1
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