We describe the task of bilingual markup transfer, which involves placing
markup tags from a source sentence into a fixed target translation.
This task arises in practice when a human translator generates the target translation without markup, and then the system infers the placement of markup tags.
This task contrasts from previous work in which markup transfer is performed jointly with machine translation.
We propose two novel metrics and evaluate several approaches based on 
unsupervised word alignments as well as a supervised neural sequence-to-sequence
model. 
Our best approach achieves an average accuracy of 94.7% across six language pairs, indicating its potential usefulness for real-world localization tasks.

Automatic Bilingual Markup Transfer

Findings Papers - Machine Translation and Multilinguality

technical paper

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EMNLP 2021

EMNLP 2021 is planned to be a hybrid event in Punta Cana, Dominican Republic, with both on-site and fully virtual participation possible.

Thomas Zenkel

1

SHORT BIO

Presentations

Automatic Bilingual Markup Transfer