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Generalized Shortest-Paths Encoders for AMR-to-Text Generation ...
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Unsupervised Bilingual Lexicon Induction Across Writing Systems ...
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Semantic Neural Machine Translation Using AMR
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 19-31 (2019) (2019)
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Abstract:
It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models. On the other hand, little work has been done on leveraging semantics for neural machine translation (NMT). In this work, we study the usefulness of AMR (abstract meaning representation) on NMT. Experiments on a standard English-to-German dataset show that incorporating AMR as additional knowledge can significantly improve a strong attention-based sequence-to-sequence neural translation model.
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doi.org/10.1162/tacl_a_00252 https://doaj.org/article/86d54844cecd4a84ace6a747a8e54b02
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Addressing the Data Sparsity Issue in Neural AMR Parsing ...
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Simultaneous Word-Morpheme Alignment for Statistical Machine Translation ...
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Simultaneous Word-Morpheme Alignment for Statistical Machine Translation ...
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Using latent information for natural language processing tasks
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On word alignment models for statistical machine translation
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