Publication Title
Impact of automatic segmentation on the quality, productivity and self-reported post-editing effort of intralingual subtitles
Publication Type
Book chapter
Title of edited book
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)
Year of publication
2016
Pages
3049-3053
Publisher
City
Language(s)

English

Modalities
Abstract
This paper describes the evaluation methodology followed to measure the impact of using a machine learning algorithm to automatically segment intralingual subtitles. The segmentation quality, productivity and self-reported post-editing effort achieved with such approach are shown to improve those obtained by the technique based in counting characters, mainly employed for automatic subtitle segmentation currently. The corpus used to train and test the proposed automated segmentation method is also described and shared with the community, in order to foster further research in this area.
Submitted by Belén Agulló on Sun, 15/09/2019 - 14:22