Evaluation of Croatian Word Embeddings

Abstract

Croatian is poorly resourced and highly inflected language from Slavic language family. Nowadays, research is focusing mostly on English. We created a new word analogy dataset based on the original English Word2vec word analogy dataset and added some of the specific linguistic aspects from the Croatian language. Next, we created Croatian WordSim353 and RG65 datasets for a basic evaluation of word similarities. We compared created datasets on two popular word representation models, based on Word2Vec tool and fastText tool. Models have been trained on 1.37B tokens training data corpus and tested on a new robust Croatian word analogy dataset. Results show that models are able to create meaningful word representation. This research has shown that free word order and the higher morphological complexity of Croatian language influences the quality of resulting word embeddings