Does Word2Vec encode human perception of similarityƒ A study in Bangla

The quest to understand how language and concepts are organized in human mind is a neverending pursuit undertaken by researchers in computational psycholinguistics; simultaneously, on the other hand, researchers have tried to quantitatively model the semantic space from written corpora and discourses through different computational approaches - while both of these interacts with each other in-terms of understanding human processing through computational linguistics and enhancing NLP methods from the insights, it has seldom been systematically studied if the two corroborates each other. In this paper, we have explored how and if the standard word embedding based semantic representation models represent the human mental lexicon. Towards that, We have conducted a semantic priming experiment to capture the psycholinguistics aspects and compared the results with a distributional word-embedding model: Bangla word2Vec. Analysis of reaction time indicates that corpus-based semantic similarity measures do not reflect the true nature of mental representation and processing of words. To the best of our knowledge this is first of a kind study in any language especially Bangla.