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- Title
Finding next of kin: Cross-lingual embedding spaces for related languages.
- Authors
Sharoff, Serge
- Abstract
Some languages have very few NLP resources, while many of them are closely related to better-resourced languages. This paper explores how the similarity between the languages can be utilised by porting resources from better- to lesser-resourced languages. The paper introduces a way of building a representation shared across related languages by combining cross-lingual embedding methods with a lexical similarity measure which is based on the weighted Levenshtein distance. One of the outcomes of the experiments is a Panslavonic embedding space for nine Balto-Slavonic languages. The paper demonstrates that the resulting embedding space helps in such applications as morphological prediction, named-entity recognition and genre classification.
- Subjects
LANGUAGE &; languages; SIMILARITY (Geometry); SPACE; RESEMBLANCE (Philosophy)
- Publication
Natural Language Engineering, 2020, Vol 26, Issue 2, p163
- ISSN
1351-3249
- Publication type
Article
- DOI
10.1017/S1351324919000354