Interlingua based neural machine translation
We propose a machine translation architecture based on autoencoders and a shared interlingua representation that produce comparable results to state of the art systems. Also we define evaluation and visualization strategies as metrics of the performance of the architecture.
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| Format: | master thesis |
| Publication Date: | 2018 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/121672 |
| Online Access: | https://hdl.handle.net/2117/121672 |
| Access Level: | Open access |
| Keyword: | Neural networks (Computer science) Machine learning deep learning autoencoders machine translation Xarxes neuronals (Informàtica) Aprenentatge automàtic Àrees temàtiques de la UPC::Informàtica |
| Summary: | We propose a machine translation architecture based on autoencoders and a shared interlingua representation that produce comparable results to state of the art systems. Also we define evaluation and visualization strategies as metrics of the performance of the architecture. |
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