Abstract Usage-based accounts of sociolinguistic learning 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. This paper presents a critical assessment of methodological implications and considerations with regard to investigating such questions, thereby focusing on the upcoming paradigm of artificial sociolinguistic language learning. Based on the available literature on this paradigm, 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. Results show relatively limited learning overall, yet the experiment points to key methodological insights, particularly regarding the role of salience and relevance in lab-based learning tasks.
Puyvelde et al. (Sun,) studied this question.