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Chinese-Catalan: A Neural Machine Translation Approach Based on Pivoting and Attention Mechanisms

Costa-Jussà, Marta R. ; Casas, Noé ; Escolano, Carlos ; Fonollosa, José A. R.

ACM transactions on Asian and low-resource language information processing, 2019, Vol.18 (4), p.1-8 [Periódico revisado por pares]

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Título:
Chinese-Catalan: A Neural Machine Translation Approach Based on Pivoting and Attention Mechanisms
Autor: Costa-Jussà, Marta R. ; Casas, Noé ; Escolano, Carlos ; Fonollosa, José A. R.
Assuntos: Aprenentatge automàtic ; Informàtica ; Intel·ligència artificial ; Machine learning ; Machine translating ; Neural networks (Computer science) ; Traducció automàtica ; Xarxes neuronals (Informàtica) ; Àrees temàtiques de la UPC
É parte de: ACM transactions on Asian and low-resource language information processing, 2019, Vol.18 (4), p.1-8
Descrição: This article innovatively addresses machine translation from Chinese to Catalan using neural pivot strategies trained without any direct parallel data. The Catalan language is very similar to Spanish from a linguistic point of view, which motivates the use of Spanish as pivot language. Regarding neural architecture, we are using the latest state-of-the-art, which is the Transformer model, only based on attention mechanisms. Additionally, this work provides new resources to the community, which consists of a human-developed gold standard of 4,000 sentences between Catalan and Chinese and all the others United Nations official languages (Arabic, English, French, Russian, and Spanish). Results show that the standard pseudo-corpus or synthetic pivot approach performs better than cascade.
Idioma: Inglês

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