Chinese-Catalan: A neural machine translation approach based on pivoting and attention mechanisms
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 neu...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/165888 |
| Acceso en línea: | https://hdl.handle.net/2117/165888 https://dx.doi.org/10.1145/3312575 |
| Access Level: | acceso abierto |
| Palabra clave: | Neural networks (Computer science) Machine learning Machine translating Aprenentatge automàtic Xarxes neuronals (Informàtica) Traducció automàtica Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
| Sumario: | 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. |
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