Departamento de
Traducción e Interpretación


Tema:   Automática.
Autor:   Popovic, Maja
Año:   2009
Título:   Machine translation: statistical approach with additional linguistic knowledge
Lugar:   Aachen
Editorial/Revista:   Rheinisch-Westfälischen Technischen Hochschule Aachen
Páginas:   127
Idioma:   Inglés.
Tipo:   Tesis.
ISBN/ISSN/DOI:   ISBN: 996867163.
Disponibilidad:   Acceso abierto.
Resumen:   In this thesis, three possible aspects of using linguistic (i.e. morpho-syntactic) knowledge for statistical machine translation are described: the treatment of syntactic differences between source and target language using source POS tags, statistical machine translation with a small amount of bilingual training data, and automatic error analysis of translation output. Reorderings in the source language based on the POS tags are systematically investigated: local reorderings of nouns and adjectives for the Spanish–English language pair and long-range reorderings of verbs for the German–English language pair. Both types of reorderings result in better performance of the translation system, local reordering being more important for the scarce training corpora. For such corpora, strategies for achieving an acceptable translation quality by applying appropriate morpho-syntactic transformations are exploited for three language pairs: Spanish– English, German–English and Serbian–English. Very scarce task-specific corpora as well as conventional dictionaries are used as bilingual training material. In addition to conventional dictionaries, the use of phrasal lexica is proposed and investigated. [Source: Author]
2001-2019 Universidad de Alicante DOI: 10.14198/bitra
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