Affect-enriched vector representation of words for use in machine-learning models

摘要

Certain embodiments involve facilitating natural language processing through enriched distributional word representations. For instance, a computing system receives an initial word distribution having initial word vectors that represent, within a multidimensional vector space, words in a vocabulary. The computing system also receives a human-reaction lexicon indicating human-reaction values respectively associated with words in the vocabulary. The computing system creates an enriched word distribution by modifying one or more of the initial word vectors such that the distance between the pair of initial word vectors representing a pair of words is decreased based on a human-reaction similarity between the pair of words.