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Input Representations for Parsing Discourse Representation Structures: Comparing English with Chinese ...
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On the Difficulty of Translating Free-Order Case-Marking Languages ...
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UDapter: Language Adaptation for Truly Universal Dependency Parsing ...
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Understanding Cross-Lingual Syntactic Transfer in Multilingual Recurrent Neural Networks ...
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Zero-shot Dependency Parsing with Pre-trained Multilingual Sentence Representations ...
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Neural versus Phrase-Based Machine Translation Quality: a Case Study ...
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Abstract:
Within the field of Statistical Machine Translation (SMT), the neural approach (NMT) has recently emerged as the first technology able to challenge the long-standing dominance of phrase-based approaches (PBMT). In particular, at the IWSLT 2015 evaluation campaign, NMT outperformed well established state-of-the-art PBMT systems on English-German, a language pair known to be particularly hard because of morphology and syntactic differences. To understand in what respects NMT provides better translation quality than PBMT, we perform a detailed analysis of neural versus phrase-based SMT outputs, leveraging high quality post-edits performed by professional translators on the IWSLT data. For the first time, our analysis provides useful insights on what linguistic phenomena are best modeled by neural models -- such as the reordering of verbs -- while pointing out other aspects that remain to be improved. ... : Conference on Empirical Methods in Natural Language Processing (EMNLP), November 1-5, 2016, Austin, Texas, USA ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1608.04631 https://dx.doi.org/10.48550/arxiv.1608.04631
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A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena ...
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