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BITRA. BIBLIOGRAFÍA DE INTERPRETACIÓN Y TRADUCCIÓN

 
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Tema:   Automática.
Autor:   Bender, Oliver
Año:   2010
Título:   Robust machine translation for multi-domain tasks
Lugar:   Aachen https://www-i6.informatik.rwth-aachen.de/publications/download/691/BenderOliver--RobustMachineTranslationforMulti-DomainTasks--2010.pdf
Editorial/Revista:   Rheinisch-Westfälischen Technischen Hochschule Aachen
Páginas:   154
Idioma:   Inglés.
Tipo:   Tesis.
Disponibilidad:   Acceso abierto.
Resumen:   In this thesis, we investigate and extend the phrase-based approach to statistical machine translation. Due to improved concepts and algorithms, the quality of the generated translation hypotheses has been signi cantly improved in recent years. Still, the translation quality leaves a lot to be desired when going beyond traditional translation tasks, such as newswire articles and when addressing more ambitious translation problems. We extend the state-of-the-art in phrase-based translation which enables us to build a robust translation system for multi-domain input. Robustness is hereby regarded as the ability to produce high quality translations for arbitrary input texts, e.g. automatic transcriptions of recognized speech or other unstructured, potentially noisy input. In this work, we focus on Arabic-English translation tasks. We study the search problem for phrase-based statistical machine translation in detail. For this, we examine the e ect of the di erent models on the translation quality. Moreover, we make an explicit distinction between reordering (coverage) and lexical hypotheses in the pruning process and stress the importance of the coverage pruning to adjust the balance between hypotheses representing di erent reorderings (coverage hypotheses) and hypotheses with different lexical representations. We present constraints to solve the reordering problem in machine translation. [Source: Author]
 
 
2001-2019 Universidad de Alicante DOI: 10.14198/bitra
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