a method for discovering computationally-derived conceptual spaces that reflect human conceptualization of musical and poetic creativity. We describe a lexical space that is defined through co-occurrence statistics, and compare the dimensions of this space with human responses on a word association task.
Participants’ responses serve as external validation of our computational findings, and frequent terms are also used as input dimensions for creating mappings from the linguistic to the conceptual domain. This novel method finds low-dimensional subspaces that represent particular conceptual regions within a vector space model of distributional semantics. Word-vectors from these discovered conceptual spaces are considered, and argued to be useful for the evaluation of creativity and creative artifacts within computational creativity