Experiment 1: He Says, She Says: A Semi-Artificial Language Learning Experiment on the Acquisition of Sociolinguistic Variation

ABSTRACT: Usage-based accounts of the acquisition of sociolinguistic variation assign a pivotal role to the frequency with which a linguistic variant and a social category co-occur in listeners’ input. However, few studies have so far compared the effects of varying frequency distributions on acquisition in a lab-based context. Based on the available literature, we designed a semi-artificial language learning experiment that manipulates the probabilistic association between a new linguistic variable and macro-social categories between participants. In a first training phase, participants were exposed to the variable – (de)voicing of the word medial stop in disyllabic pseudowords – produced by two male and two female sounding speakers (social categories of ‘gender’). Participants’ learning of the link between the linguistic variable and perceived speaker gender was subsequently tested in a perception task which also tested the generalisation of learning to words that participants did not hear during training. While results show relatively limited learning overall, the experiment points to key methodological insights that can serve as a pivot for the future of the artificial sociolinguistic language learning paradigm.