English language and linguistics research seminar: Esme Richardson-Owen, Salzburg University: Predicting how sensory adjectives combine with nouns: what can quantitative methods tell us?

In recent years there has been an increased interest in how words with the potential to express sensory experience function in language (e.g., van de Weijer, Bianchi & Paradis, 2024; Caballero & Paradis, 2023; Hartman & Paradis, 2023; Winter 2019).

In this talk, I present the results of an empirical study conducted as part of my wider PhD project that concerns sensory adjectives and their meaning potentials to express sensory experiences when they combine with nouns.  The study I present is a first step into uncovering the meaning potentials of adjective-noun constructions using a fine-grained cognitive semantic approach (Paradis, 2005).

The study makes use of existing large-scale quantitative rating studies that provide sensory data for both adjectives (Lynott & Connell, 2009) and nouns (Lynott et al., 2020; Brysbaert et al., 2014) along with new corpus data from the British National Corpus 2014 (Brezina et al., 2021; Love et al., 2017) to answer the question of whether the perceptual strength ratings of sensory adjective both correlate to and predict how the adjective combines with nouns in language usage.

The results of the statistical analyses carried out indicate that there is a correlation between the perceptual rating strengths of the sensory adjectives and how they combine with nouns.  Moreover, regression analyses suggest a pattern to how certain properties of the adjective predict how it combines with nouns in language usage: strong intradomain relationships are seen (i.e., visual ratings affect the number of visual collocates) across all sensory modalities, while interdomain effects show more complex patterns. However, of all predictors, adjective frequency is shown to be the most robust across all models. 

After presenting this initial study, I will talk briefly about how I plan to move forward with the topic and appreciate any useful feedback or ideas that you may have.