Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Beatrice Savoldi"'
Publikováno v:
Hermes, Iss 63 (2024)
Machine Translation (MT) continues to make significant strides in quality and is increasingly adopted on a larger scale. Consequently, analyses have been redirected to more nuanced aspects, intricate phenomena, as well as potential risks that may ari
Externí odkaz:
https://doaj.org/article/ec438b749ff847c796d4dd81a3f6857c
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 9, Pp 845-874 (2021)
AbstractMachine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, processing, and communicating information. However, it can suffer from biases that harm users and society at large. As a rela
Externí odkaz:
https://doaj.org/article/ebea9608538e4b829ead431e045f7af0
Gender bias is largely recognized as a problematic phenomenon affecting language technologies, with recent studies underscoring that it might surface differently across languages. However, most of current evaluation practices adopt a word-level focus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4abf1eacbd8e92fab55df8e3ce048480
Publikováno v:
Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing (GeBNLP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4e39e48c7abaacde20a4643df090e0a
https://doi.org/10.18653/v1/2022.gebnlp-1.12
https://doi.org/10.18653/v1/2022.gebnlp-1.12
Machine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, elaborating and communicating information. However, it can suffer from biases that harm users and society at large. As a relatively n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::781edfa24fdf3a5b45fec1d2dace178e
https://hdl.handle.net/11572/330101
https://hdl.handle.net/11572/330101
Autor:
Marco Turchi, Roldano Cattoni, Matteo Negri, Mattia Antonino Di Gangi, Luisa Bentivogli, Beatrice Savoldi
Publikováno v:
ACL
Translating from languages without productive grammatical gender like English into gender-marked languages is a well-known difficulty for machines. This difficulty is also due to the fact that the training data on which models are built typically ref
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b8833ce5b570711e2b4f3f9de9abfcf
http://arxiv.org/abs/2006.05754
http://arxiv.org/abs/2006.05754
Publikováno v:
COLING
In automatic speech translation (ST), traditional cascade approaches involving separate transcription and translation steps are giving ground to increasingly competitive and more robust direct solutions. In particular, by translating speech audio dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c3a00cf0ef1f8ee9471fb74dbc0d247