Towards a methodology for evaluating automatic subtitling

Alina Karakanta, Luisa Bentivogli, Mauro Cettolo, Matteo Negri, Marco Turchi


Abstract
In response to the increasing interest towards automatic subtitling, this EAMT-funded project aimed at collecting subtitle post-editing data in a real use case scenario where professional subtitlers edit automatically generated subtitles. The post-editing setting includes, for the first time, automatic generation of timestamps and segmentation, and focuses on the effect of timing and segmentation edits on the post-editing process. The collected data will serve as the basis for investigating how subtitlers interact with automatic subtitling and for devising evaluation methods geared to the multimodal nature and formal requirements of subtitling.
Anthology ID:
2022.eamt-1.57
Volume:
Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
Month:
June
Year:
2022
Address:
Ghent, Belgium
Editors:
Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
335–336
Language:
URL:
https://aclanthology.org/2022.eamt-1.57
DOI:
Bibkey:
Cite (ACL):
Alina Karakanta, Luisa Bentivogli, Mauro Cettolo, Matteo Negri, and Marco Turchi. 2022. Towards a methodology for evaluating automatic subtitling. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 335–336, Ghent, Belgium. European Association for Machine Translation.
Cite (Informal):
Towards a methodology for evaluating automatic subtitling (Karakanta et al., EAMT 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/add_acl24_videos/2022.eamt-1.57.pdf