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dc.contributor.author | Peris-Abril, Álvaro | es_ES |
dc.contributor.author | Casacuberta Nolla, Francisco | es_ES |
dc.date.accessioned | 2020-06-03T05:53:18Z | |
dc.date.available | 2020-06-03T05:53:18Z | |
dc.date.issued | 2018-09-10 | es_ES |
dc.identifier.issn | 0032-6585 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/145118 | |
dc.description.abstract | [EN] We present NMT-Keras, a flexible toolkit for training deep learning models, which puts a particular emphasis on the development of advanced applications of neural machine translation systems, such as interactive-predictive translation protocols and long-term adaptation of the translation system via continuous learning. NMT-Keras is based on an extended version of the popular Keras library, and it runs on Theano and TensorFlow. State-of-the-art neural machine translation models are deployed and used following the high-level framework provided by Keras. Given its high modularity and flexibility, it also has been extended to tackle different problems, such as image and video captioning, sentence classification and visual question answering. | es_ES |
dc.description.sponsorship | Much of our Keras fork and the Multimodal Keras Wrapper libraries were developed together with Marc Bolaños. We also acknowledge the rest of contributors to these open-source projects. The research leading this work received funding from grants PROMETEO/2018/004 and CoMUN-HaT - TIN2015-70924-C2-1-R. We finally acknowledge NVIDIA Corporation for the donation of GPUs used in this work. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Univerzita Karlova | es_ES |
dc.relation.ispartof | The Prague Bulletin of Mathematical Linguistics | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Neural Machine Translation | es_ES |
dc.subject.classification | LENGUAJES Y SISTEMAS INFORMATICOS | es_ES |
dc.title | NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.2478/pralin-2018-0010 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//PROMETEO%2F2018%2F004/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2015-70924-C2-1-R/ES/CONTEXTO, MULTIMODALIDAD Y COLABORACION DEL USUARIO EN PROCESADO DE TEXTO MANUSCRITO/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació | es_ES |
dc.description.bibliographicCitation | Peris-Abril, Á.; Casacuberta Nolla, F. (2018). NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning. The Prague Bulletin of Mathematical Linguistics. 111:113-124. https://doi.org/10.2478/pralin-2018-0010 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.2478/pralin-2018-0010 | es_ES |
dc.description.upvformatpinicio | 113 | es_ES |
dc.description.upvformatpfin | 124 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 111 | es_ES |
dc.relation.pasarela | S\368399 | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |