Abstract
This paper proposes an approach for performing bilingual dictionary generation even when trained on widely available comparable bilingual corpora. We also show its capability to provide cross-lingual similarity estimates that correlate well with human judgments. We implement an approach using a nonlinear bilingual translation model that we train using comparable corpora. We propose a method using word embeddings and kernel approximation to train scalable nonlinear transformations. We demonstrate that this novel method works better on a majority of evaluated language pairs.
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Acknowledgements
This work was supported by the Slovenian Research Agency and the IST Programme of the EC under XLike (ICT-STREP-288342), LT-Web (ICT-287815-CSA) and RENDER (ICT-257790-STREP).
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Štajner, T., Mladenić, D. Cross-lingual document similarity estimation and dictionary generation with comparable corpora. Knowl Inf Syst 58, 729–743 (2019). https://doi.org/10.1007/s10115-018-1179-9
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DOI: https://doi.org/10.1007/s10115-018-1179-9