In recent years, converging evidence has suggested that prediction plays a role in language comprehension, as it appears to do in information processing in a range of cognitive domains. Much of the evidence for this comes from the N400, a neural index of the processing of meaningful stimuli which has been argued to index the extent to which a word…

This dissertation features a relative clause island, whose status has been known to differ significantly across languages and extraction types. By conducting a series of acceptability judgment experiments with human participants, as well as measuring token-by-token surprisal values among large language models, I demonstrate the following: First,…

Although computational models can simulate aspects of human sentence processing, research on this topic has remained almost exclusively limited to the single language case. The current review presents an overview of the state of the art in computational cognitive models of sentence processing, and discusses how recent sentence-processing models…

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…

In this dissertation, I establish a research program that uses computational modeling as a testbed for theories of phonological learning. This dissertation focuses on a fundamental question: how do children acquire sound patterns from noisy, real-world data, especially in the presence of lexical exceptions that defy regular patterns? For instance,…

In this dissertation, I investigate how people navigate ambiguity in everyday speech, with a focus on quantifier-negation sentences. Combining corpus analysis, behavioral experiments, and computational modeling in the Rational Speech Act framework, I explore preferred interpretations of quantifier-negation and examine the contexts and prosodies…

Multisyllabic words constitute a large portion of children's vocabulary. However, the relationship between phonological neighborhood density and English multisyllabic word learning is poorly understood. We examine this link in three, four and six year old children using a corpus-based approach. While we were able to replicate the well-accepted…

Speakers display considerable variability in language use and representations: they may have different pronunciations of the same word, different intended meanings for the same phrases, and different sets of syntactic constraints in their internalized grammars. Comprehenders adapt to such variability by constantly updating their expectations for…

This study applies the Apriori algorithm to analyse patterns, syntactic structures, and thematic clusters in Chinese studies data from various genres. This study aims to identify recurring linguistic elements in order to shed light on the dynamic nature of the Chinese language across different contexts and time periods. The Apriori algorithm is…

Technological advances have made the ability to translate no longer exclusively belong to humans. Today, machine translation has turned into a tool with superior performance to convert text between languages without the need for human intervention. One of the translation research foci is the studies of causative translation, especially from…

The world's linguistic diversity is severely underrepresented in research on cognitive and neural aspects of language processing, with great consequences for our understanding of the relationship between language, cognition, and the human brain. The practical challenges of carrying out neurophysiological (but also behavioral) experiments under…

Artificial intelligence has evolved since its inception in the 1950s, resulting in the creation of large language models that are trained on extensive data sets to understand and generate content, such as OpenAI's ChatGPT, which launched in November 2022. Modern technology that is easy to access and free to use, like ChatGPT, is changing the…

Many datasets resulting from participant ratings for word norms and also concreteness ratios are available. However, the concreteness information of infrequent words and non-words is rare. This work aims to propose a model for estimating the concreteness of infrequent and new lexicons. Here, we used Lancaster sensory-motor word norms to predict…

Most words in natural languages are polysemous; that is, they have related but different meanings in different contexts. This one-to-many mapping of form to meaning presents a challenge to understanding how word meanings are learned, represented, and processed. Previous work has focused on solutions in which multiple static semantic…

This paper explores the processes underlying verb metaphoric extension. Work on metaphor processing has largely focused on noun metaphor, despite evidence that verb metaphor is more common. Across three experiments, we collected paraphrases of simple intransitive sentences varying in semantic strain--for example, "The motor complained"…