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dc.contributor.authorOkinina N
dc.contributor.authorNicolas L
dc.date.accessioned2019-02-14T13:59:45Z
dc.date.available2019-02-14T13:59:45Z
dc.date.issued2018
dc.identifier.urihttp://www.aaccademia.it/scheda-libro?aaref=1259
dc.identifier.urihttp://hdl.handle.net/10863/8193
dc.description.abstractWe present the results of prototypical experiments conducted with the goal of designing a machine translation (MT) based system that assists the annotators of learner corpora in performing orthographic error annotation. When an annotator marks a span of text as erroneous, the system suggests a correction for the marked error. The presented experiments rely on word-level and character-level Statistical Machine Translation (SMT) systems.en_US
dc.languageEnglish
dc.language.isoenen_US
dc.relationFifth Italian Conference on Computational Linguistics ; Torino : 10.12.2018 - 12.12.2018
dc.rights
dc.subjectmachine translationen_US
dc.subjecterror correction
dc.subjectlearner corpora
dc.titleTowards SMT-Assisted Error Annotation of Learner Corporaen_US
dc.typeBook chapteren_US
dc.date.updated2019-02-14T13:48:44Z
dc.publication.title
dc.language.isiEN-GB
dc.description.fulltextopenen_US


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