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Mapping word embeddings of different languages into a single space has multiple applications. In order to map from a source space into a target space, a common approach is to learn a linear mapping that minimizes the distances between equivalences listed in a bilingual dictionary. In this paper, we propose a framework that generalizes previous work,(More)
The goal of this FP7 European project is to contribute for the advancement of quality machine translation by pursuing an approach that further relies on semantics, deep parsing and linked open data. 1 Summary QTLeap project (Quality Translation by Deep Language Engineering Approaches) is a collaborative project funded by the European Commission(More)
Translation of named-entities (NEs) is an issue in SMT. In this paper we analyze the errors when translating NEs with a SMT system from English to Spanish. We train on Europarl and test on News Commentary, fo-cusing on entities correctly recognized by an automatic NE recognition system. The automatic systems translate around 85% NEs correctly , leaving a(More)
Resumen: En este trabajo se describe la participación del grupo IXA de la UPV/EHU en la tarea sobre Traducción de Tweets en el congreso de la SEPLN (TweetMT 2015). Se han adaptado dos sistemas previamente desarrollados para la traducción es-eu y eu-es, obteniéndose buenos resultados (mejores que otros publicados previamente). Se describe la recopilación de(More)
This paper presents a hybrid machine translation framework based on a pre-processor that translates fragments of the input text by using example-based machine translation techniques. The pre-processor resembles a translation memory with named-entity and chunk generalization , and generates a high quality partial translation that is then completed by the(More)
Deep-syntax approaches to machine translation have emerged as an alternative to phrase-based statistical systems. TectoMT is an open source framework for transfer-based MT which works at the deep tectogrammatical level and combines linguistic knowledge and statistical techniques. When adapting to a domain, terminological resources improve results with(More)
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