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Automatic Bilingual Markup Transfer ...
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Abstract:
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. ...
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URL: https://underline.io/lecture/38424-automatic-bilingual-markup-transfer https://dx.doi.org/10.48448/5ynm-s029
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Adding Interpretable Attention to Neural Translation Models Improves Word Alignment ...
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Comparison of Data Selection Techniques for the Translation of Video Lectures
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In: The eleventh biennial conference of the Association for Machine Translation in the Americas (AMTA-2014) ; https://hal.archives-ouvertes.fr/hal-01157888 ; The eleventh biennial conference of the Association for Machine Translation in the Americas (AMTA-2014), AMTA, Oct 2014, Vancouver, Canada (2014)
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