Abstract
Few approaches to extract word translations from non-parallel texts have been proposed so far. Researchers have not been encouraged to work on this topic because extracting information from non-parallel corpora is a difficult task producing poor results. Whereas for parallel texts, word translation extraction can reach about 99%, the accuracy for non-parallel texts has been around 72% up to now. The current approach, which relies on the previous extraction of bilingual pairs of lexico-syntactic templates from parallel corpora, makes a significant improvement to about 89% of words translations identified correctly.
Keywords
- Test Word
- Computational Linguistics
- Parallel Corpus
- Correct Translation
- Bilingual Dictionary
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This work has been supported by Ministerio de Educación y Ciencia of Spain, within the project GARI-COTERM, ref: HUM2004-05658-D02-02.
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Otero, P.G., Campos, J.R.P. (2005). An Approach to Acquire Word Translations from Non-parallel Texts. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_59
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DOI: https://doi.org/10.1007/11595014_59
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