Lexical and affective models in early acquisition of semantics

Abstract

Motivated by theories of early language development in children we investigate the contribution of affective features to early acquisition of lexical semantics. For the task of semantic similarity between words, semantic and affective spaces are modeled using network-based distributed semantic models. We propose a method for constructing semantic activations from a combination of lexical and affective relations and show that affective information plays a prominent role in our lexical development model.

Neuroimaging of valence decisions in children and adults

“…Supporting neurocognitive evidence for the idea of a valence representation based on associations in cortical lexico-semantic networks came from a study using the VDT suggesting that word valence is partially derived from distributional information ( Kuhlmann et al, 2017 ). Computational evidence furthermore suggests that the exploitation of affective activations facilitates the acquisition of lexical semantics in children ( Kolovou et al, 2017 ).…”