Experimental Approaches to Syntactic Optionality (ExSynOp)

The natural languages of the world are characterized by largely rigid, often highly idiosyncratic rule systems. Within any given language, it is hard to find instances of true optionality (i.e. a many-to-one mapping from form to meaning). The ExSynOp project sets out to explore this central puzzle: what drives the evolution of complex, rigid rule systems in natural languages? We do this by investigating the sources of regularisation, i.e., the reduction of variation in a language. Our focus on regularisation will bring new insights to one of the most debated issues in linguistics: are languages shaped predominantly by the usage patterns of adults (evident in processing, register/style choices, MacDonald 2013, Bybee 2015), or the learning preferences/limitations of children (Clark 1987, Newport 2005, Yang 2017, Chomsky 1986)? This project takes as its starting point a unique naturally-occurring case study in (apparent) optionality: word order variation in the closely related Mainland Scandinavian languages and varieties. We have identified four word order variables where at least one variety shows optionality, and another a strict rule: subject shift, particle shift, object shift and long object shift. By studying acquisition (L1 child and L2 adult), and processing (production/comprehension) of variable and non-variable grammars in the context of closely related languages, we can identify where preferences for regular systems arise. We will address three fundamental issues in the establishment of rigid grammars: (1) are there processing benefits (or costs) associated with categorical rules; (2) is the L1 language learner pre-disposed to categorical rules, or do categorical tendencies develop later and (3) is low-frequent syntactic variation in speakers conditioned by register/dialect? To address these issues, we will use novel large-scale experiments for speech elicitations, combined with methods for text-speech alignment, which will be developed within the project.

The research Council of Norway: FRIPRO

Grant amount: 10.8 MNOK