Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation
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| Natura: | Artículo científico |
| Lingua: | en |
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Instituto Politécnico Nacional
2015
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| _version_ | 1876467130130497536 |
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| author | Rahma Sellami |
| author_facet | Rahma Sellami |
| contents | Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation Rahma Sellami Fatima Deffaf Fatiha Sadat Lamia Hadrich Belguith Computación Named entity pivot language machine translation One of the existing difficulties in natural lan- guage processing applications is the lack of appropri- ate tools for the recognition, translation, and/or translit- eration 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. Eval- uations on the Arabic-French pair of languages using English as pivot in the transitive model showed the ef- fectiveness 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. 2015 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61543181007 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.4 Vol.19 |
| format | Artículo científico |
| id | redalyc_61543181007 |
| institution | Redalyc |
| language | en |
| publishDate | 2015 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation Rahma Sellami Computación Named entity pivot language machine translation Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation Rahma Sellami Fatima Deffaf Fatiha Sadat Lamia Hadrich Belguith Computación Named entity pivot language machine translation One of the existing difficulties in natural lan- guage processing applications is the lack of appropri- ate tools for the recognition, translation, and/or translit- eration 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. Eval- uations on the Arabic-French pair of languages using English as pivot in the transitive model showed the ef- fectiveness 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. 2015 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61543181007 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.4 Vol.19 |
| title | Improved Statistical Machine Translation by Cross-Linguistic Projection of Named Entities Recognition and Translation |
| topic | Computación Named entity pivot language machine translation |
| url | https://www.redalyc.org/articulo.oa?id=61543181007 |