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Subword Mapping and Anchoring across Languages ...
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Subword Mapping and Anchoring across Languages ...
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Subword Mapping and Anchoring across Languages ...
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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation ...
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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation ...
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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation ...
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Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss German ...
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DiscoMT 2016 Shared Task on Cross-lingual Pronoun Prediction
Guillou, Liane; Hardmeier, Christian; Nakov, Preslav. - : Uppsala University, 2017
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Consistent Translation of Repeated Nouns using Syntactic and Semantic Cues ...
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Multilingual Hierarchical Attention Networks for Document Classification ...
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The Summa Platform Prototype ...
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Multilingual Hierarchical Attention Networks for Document Classification ...
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Multilingual Hierarchical Attention Networks for Document Classification ...
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The Summa Platform Prototype ...
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Machine Translation of Spanish Personal and Possessive Pronouns Using Anaphora Probabilities ...
Luong, Ngoc Quang; Popescu-Belis, Andrei; Rios Gonzales, Annette. - : Association for Computational Linguistics, 2017
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Self-Attentive Residual Decoder for Neural Machine Translation ...
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Sense-Aware Statistical Machine Translation using Adaptive Context-Dependent Clustering ...
Abstract: Statistical machine translation (SMT) systems use local cues from n-gram translation and language models to select the translation of each source word. Such systems do not explicitly perform word sense disambiguation (WSD), although this would enable them to select translations depending on the hypothesized sense of each word. Previous attempts to constrain word translations based on the results of generic WSD systems have suffered from their limited accuracy. We demonstrate that WSD systems can be adapted to help SMT, thanks to three key achievements: (1)~we consider a larger context for WSD than SMT can afford to consider; (2)~we adapt the number of senses per word to the ones observed in the training data using clustering-based WSD with K-means; and (3)~we initialize sense-clustering with definitions or examples extracted from WordNet. Our WSD system is competitive, and in combination with a factored SMT system improves noun and verb translation from English to Chinese, Dutch, French, German, and Spanish. ...
URL: https://zenodo.org/record/834304
https://dx.doi.org/10.5281/zenodo.834304
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Sense-Aware Statistical Machine Translation using Adaptive Context-Dependent Clustering ...
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19
Multilingual Hierarchical Attention Networks for Document Classification
In: http://infoscience.epfl.ch/record/231134 (2017)
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Cross-lingual Transfer for News Article Labeling: Benchmarking Statistical and Neural Models
In: http://infoscience.epfl.ch/record/231130 (2017)
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