In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via…

Speech is highly variable and systematic, governed by the internal linguistic system and socio-indexical factors. The systematic relationship of socio-indexical factors and variable phonetic forms, referred to here as "socio-indexical structure," has been the cornerstone of sociophonetic research over the last several decades. Research…

The past two decades have shown an unexpected effectiveness of "Web-scale" data in natural language processing. Even the simplest models, when paired with unprecedented amounts of unstructured and unlabeled Web data, have been shown to outperform sophisticated ones. It has been argued that the effectiveness of Web-scale data has…

This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we…

Topic models like latent Dirichlet allocation (LDA) provide a framework for analyzing large datasets where observations are collected into groups. Although topic modeling has been fruitfully applied to problems social science, biology, and computer vision, it has been most widely used to model datasets where documents are modeled as exchangeable…

Learning a phonetic category (or any linguistic category) requires integrating different sources of information. A crucial unsolved problem for phonetic learning is how this integration occurs: how can we update our previous knowledge about a phonetic category as we hear new exemplars of the category? One model of learning is Bayesian Inference,…