Şenel, Lütfü KeremYücesoy, V.Koç, A.Çukur, Tolga2018-04-122018-04-122017http://hdl.handle.net/11693/37656Date of Conference: 5-7 July 2017Conference Name: 40th International Conference on Telecommunications and Signal Processing, TSP 2017This paper studies cross-lingual semantic similarity (CLSS) between five European languages (i.e. English, French, German, Spanish and Italian) via unsupervised word embeddings from a cross-lingual lexicon. The vocabulary in each language is projected onto a separate high-dimensional vector space, and these vector spaces are then compared using several different distance measures (i.e., correlation, cosine etc.) to measure their pairwise semantic similarities between these languages. A substantial degree of similarity is observed between the vector spaces learned from corpora of the European languages. Null hypothesis testing and bootstrap methods (by resampling without replacement) are utilized to verify the results.EnglishCross-lingual semantic similarityLanguage modelsNatural language processingSemantic similarityWord embeddingNatural language processing systemsConference Paper10.1109/TSP.2017.8076005