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A High-Quality Multilingual Dataset for Structured Documentation Translation ...
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Abstract:
This paper presents a high-quality multilingual dataset for the documentation domain to advance research on localization of structured text. Unlike widely-used datasets for translation of plain text, we collect XML-structured parallel text segments from the online documentation for an enterprise software platform. These Web pages have been professionally translated from English into 16 languages and maintained by domain experts, and around 100,000 text segments are available for each language pair. We build and evaluate translation models for seven target languages from English, with several different copy mechanisms and an XML-constrained beam search. We also experiment with a non-English pair to show that our dataset has the potential to explicitly enable $17 \times 16$ translation settings. Our experiments show that learning to translate with the XML tags improves translation accuracy, and the beam search accurately generates XML structures. We also discuss trade-offs of using the copy mechanisms by ... : Published at WMT2019; the draft has been updated with our dataset's URL: https://github.com/salesforce/localization-xml-mt ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2006.13425 https://arxiv.org/abs/2006.13425
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Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ...
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Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ...
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Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering ...
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Multilingual Extractive Reading Comprehension by Runtime Machine Translation ...
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Adaptive Joint Learning of Compositional and Non-Compositional Phrase Embeddings ...
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A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks ...
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Task-Oriented Learning of Word Embeddings for Semantic Relation Classification ...
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