TY - JOUR
KW - Immaterial culture
KW - Machine translation
KW - Neural machine translation
KW - Post-editese
KW - Translation quality
KW - Translationese
AU - Pilar Sanchez-Gijon
AU - Ramon Huerta
AB - This article deals with the consequences of using a neural machine translation trained from corpora compiled from translations of specific text genres produced in particular professional contexts. Phenomena such as translationese and post-editese, associated with the use of machine translation, underline the need to orient research towards new approaches to the question of professional translation quality. Working from the viewpoint that languages should be safeguarded as intangible cultural heritage, it poses a range of questions related to the impact of machine translation on target cultures and languages: how it is perceived, quality and how its use can alter the standard language. It points out the need to define translation quality thresholds that go beyond the aspects most commonly related to error detection, which is the most economically viable type of correction.
BT - Revista tradumàtica: traducció i tecnologies de la informació i la comunicació
DA - dec
DO - 10.5565/rev/tradumatica.277
LA - Catalan
M1 - 18
N1 - Publisher: Departament de Traducció i d Interpretació Section: Revista tradumàtica: traducció i tecnologies de la informació i la comunicació
N2 - This article deals with the consequences of using a neural machine translation trained from corpora compiled from translations of specific text genres produced in particular professional contexts. Phenomena such as translationese and post-editese, associated with the use of machine translation, underline the need to orient research towards new approaches to the question of professional translation quality. Working from the viewpoint that languages should be safeguarded as intangible cultural heritage, it poses a range of questions related to the impact of machine translation on target cultures and languages: how it is perceived, quality and how its use can alter the standard language. It points out the need to define translation quality thresholds that go beyond the aspects most commonly related to error detection, which is the most economically viable type of correction.
PY - 2020
SP - 1
EP - 10
T2 - Revista tradumàtica: traducció i tecnologies de la informació i la comunicació
TI - Conseqüències de la traducció automàtica neuronal sobre les llengües d arribada
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101003665&doi=10.5565%2fREV%2fTRADUMATICA.277&partnerID=40&md5=1c6c64970e6c0e1c3da5ddb974754e3b
SN - 15787559 (ISSN)
ER -