Next Wednesday, Amy will present her project on Empirical Learnability and Inference with Minimalist Grammars, which is the second part of the presentation that she did at the end of last semester.
Abstract: This is a draft presentation of some of my current PhD research, intended for a more computationally-oriented audience. It contains collaborative work done over the past year with Eva Portelance (Stanford), Daniel Harasim (EPFL), and Leon Bergen (UCSD). Minimalist Grammars are a lexicalied grammar formalism inspired by Chomsky’s (1994) Minimalist Program, and as such are well suited to formalize theories in contemporary syntactic theory. Our work formulate a learning model based on the technique of Variational Bayesian Inference and apply the model to pilot experiments. In this presentation, I focus on giving an introduction to the central issues in syntactic theory and motivating the problems we wish to address. I give an introduction to syntactic theory and formal grammars, and demonstrate why context free grammars are insufficient to adequately characterize natural language. Minimalist Grammars, a lexicalized mildly context-sensitive formalism are introduced as a more linguistically adequate formalism.