LLS Colloquium: Towards a model of linguistic malleability across the lifespan: exploring the realisation of FACE and GOAT in panel data

On Wednesday 20th April 2022, James Grama, Isabelle Buchstaller, Mirjam E. Eiswirth and Lea Bauernfeind (University of Duisburg-Essen) will be presenting on "A model of linguistic malleability across the lifespan", looking at the realisation of FACE and GOAT in panel data. This is work in collaboration with Isabelle Buchstaller and Mirjam E. Eiswirth (Duisburg University).

Towards a model of linguistic malleability across the lifespan: exploring the realisation of FACE and GOAT in panel data

The vowels of Tyneside English have a long history of sociolinguistic investigation (Milroy et al. 1994; Watt 1998; Beal et al. 2012; Warburton 2020). Ongoing research by the TUULS project (Llamas et al. 2017) for example, has been investigating the extent to which geographical mobility across the lifespan in older speakers impacts their use of localized forms. However, previous findings have largely been based on apparent time analyses or induced from comparisons with legacy data. This paper explores the extent to which speakers follow the trajectories in the Northern vowel system observed in the community across their own lifespan.

We report on a novel panel corpus which covers 12 speakers from Tyneside in a complex dynamic design. We combine acoustic and auditory analysis to report on approximately 8,000 tokens of two locally salient vowels in the North East—FACE and GOAT—across three time slices. Preliminary results suggest that individual social trajectories constrain linguistic choices in an age-graded fashion. The present paper enriches the understanding of how sound changes progress within individual speakers.

The talk will take place at 4pm on Zoom, and there will be an opportunity to ask questions at the end. Please sign up to receive a zoom invite at this link. 

Event poster: LLS Colloquium: Towards a model of linguistic malleability across the lifespan: exploring the realisation of FACE and GOAT in panel data (PDF)