https://lling.univ-nantes.fr/medias/photo/image-seminaire-synsem-last_1634558885025-JPG
  • Le 26 novembre 2021 de 14:00 à 17:00
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  • Vendredi 26 novembre 2021, 14h 
Responsable : Mora Maldonado (U. Pompeu Fabra)
Titre : How to use artificial language learning experiments to investigate typological tendencies in semantics


Abstract:
One of the fundamental goals of generative linguistics is to identify a set of principles that constrain our linguistic capacity, and thereby shape the distribution of possible linguistic patterns. However, this idea remains contentious both within linguistics and in the broader cognitive science community. One of the problems is that traditionally, the data that have been used to support the existence of such principles have come from introspective judgments, language descriptions (grammars) and typology samples. None of these types of data are particularly good for establishing causal links between human cognition or learning and the (non-)existence of particular linguistic patterns. In this talk, I will highlight how subtle predictions of linguistic theories can be investigated through Artificial Language Learning (ALL) experiments. I first introduce this approach by presenting a study where we combine artificial language learning experiments with modelling tools to explore theoretical predictions about person pronoun systems (Maldonado & Culbertson 2021a; Zaslavsky, Maldonado and Culbertson, 2021). I then present in detail a series of experiments which takes the use of ALL to the next level, by investigating a complex, theoretically rich phenomenon which falls at the intersection between phonology, morphology, syntax and semantics. Specifically, how languages express negation and negative dependencies (i.e., how negative words interact with one another; Maldonado & Culbertson, 2021b). Our findings, though still preliminary, present a first step in understanding how negative concord and double negation are learned, and thus how these patterns might be constrained.