Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation
Título del documento: Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation
Revista: Computación y sistemas
Base de datos: PERIÓDICA
Número de sistema: 000395007
ISSN: 1405-5546
Autores: 1
2
2
1
Instituciones: 1University of Sfax, MIRACL Laboratory, Sfax. Túnez
2Universite du Quebec a Montreal, Montreal, Quebec. Canadá
Año:
Periodo: Oct-Dic
Volumen: 19
Número: 4
Paginación: 701-711
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Analítico
Resumen en inglés One of the existing difficulties in natural language processing applications is the lack of appropritate tools for the recognition, translation, and/or transliteration of named entities (NEs), specifically for less- resourced languages. In this paper, we propose a new method to automatically label multilingual parallel data for Arabic-French pair of languages with named entity tags and build lexicons of those named entities with their transliteration and/or translation in the target language. For this purpose, we bring in a third well-resourced language, English, that might serve as pivot, in order to build an Arabic-French NE Translation lexicon. Evaluations on the Arabic-French pair of languages using English as pivot in the transitive model showed the effectiveness of the proposed method for mining Arabic- French named entities and their translations. Moreover, the integration of this component in statistical machine translation outperformed the baseline system
Disciplinas: Ciencias de la computación,
Literatura y lingüística
Palabras clave: Procesamiento de datos,
Lingüística aplicada,
Traducción,
Procesamiento de lenguaje natural,
Nombres de entidades,
Reconocimiento,
Arabe,
Francés,
Traducción automática,
Lingüística computacional
Keyword: Computer science,
Literature and linguistics,
Data processing,
Applied linguistics,
Translation,
Natural language processing,
Named entities,
Recognition,
Arabic,
French,
Machine translation,
Computing linguistics
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