  Conjuring up our thoughts, language reflects statistical patterns of word
co-occurrences which in turn come to describe how we perceive the world.
Whether counting how frequently nouns and verbs combine in Google search
queries, or extracting eigenvectors from term document matrices made up of
Wikipedia lines and Shakespeare plots, the resulting latent semantics capture
not only the associative links which form concepts, but also spatial dimensions
embedded within the surface structure of language. As both the shape and
movements of objects have been found to be associated with phonetic contrasts
already in toddlers, this study explores whether articulatory and acoustic
parameters may likewise differentiate the latent semantics of action verbs.
Selecting 3 x 20 emotion, face, and hand related verbs known to activate
premotor areas in the brain, their mutual cosine similarities were computed
using latent semantic analysis LSA, and the resulting adjacency matrices were
compared based on two different large scale text corpora; HAWIK and TASA.
Applying hierarchical clustering to identify common structures across the two
text corpora, the verbs largely divide into combined mouth and hand movements
versus emotional expressions. Transforming the verbs into their constituent
phonemes, the clustered small and large size movements appear differentiated by
front versus back vowels corresponding to increasing levels of arousal. Whereas
the clustered emotional verbs seem characterized by sequences of close versus
open jaw produced phonemes, generating up- or downwards shifts in formant
frequencies that may influence their perceived valence. Suggesting, that the
latent semantics of action verbs reflect parameters of intensity and emotional
polarity that appear correlated with the articulatory contrasts and acoustic
characteristics of phonemes
