Cross-Lingual Lexico-Semantic Transfer in Language Learning
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics
54th Annual Meeting of the Association for Computational Linguistics
Association for Computational Linguistics
Volume 1: Long Papers
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Kochmar, E., & Shutova, E. (2016). Cross-Lingual Lexico-Semantic Transfer in Language Learning. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Volume 1: Long Papers 974-983. https://doi.org/10.17863/CAM.9707
Lexico-semantic knowledge of our native language provides an initial foundation for second language learning. In this paper, we investigate whether and to what extent the lexico-semantic models of the native language (L1) are transferred to the second language (L2). Specifically, we focus on the problem of lexical choice and investigate it in the context of three typologically diverse languages: Russian, Spanish and English. We show that a statistical semantic model learned from L1 data improves automatic error detection in L2 for the speakers of the respective L1. Finally, we investigate whether the semantic model learned from a particular L1 is portable to other, typologically related languages.
Ekaterina Kochmar’s research is supported by Cambridge English Language Assessment via the ALTA Institute. Ekaterina Shutova’s research is supported by the Leverhulme Trust Early Career Fellowship.
This record's DOI: https://doi.org/10.17863/CAM.9707
This record's URL: https://www.repository.cam.ac.uk/handle/1810/264290