German-speaking children between ages 2 and 3 mostly use the preposition ohne ('without') in an adult-like way, to express the absence of something. In this article we present surprising results from a corpus study suggesting that in this age group, absence can also be expressed using the sequence mit ohne 'with without'. We argue that this…

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,…

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,…

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…

This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing 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…

Research on modality shifts in English-to-Chinese courtroom translation remains limited, despite the critical role of modality in shaping legal nuance, and speaker intentionality in judicial settings. This gap is particularly consequential in high-stakes contexts such as the International Military Tribunal for the Far East (IMTFE), where…

While evidence has accumulated to support the argument of shared computational mechanisms underlying language comprehension between humans and large language models (LLMs), few studies have examined this argument beyond native-speaker populations. This study examines whether and how alignment between LLMs and human brains captures the homogeneity…

In this study, we use temporally aligned word embeddings and a large diachronic corpus of English to quantify language change in a data-driven, scalable way, which is grounded in language use. We show a unique and reliable relation between measures of language change and age of acquisition ("AoA") while controlling for frequency,…

Linguistic meaning is generated by the mind and can be expressed in multiple languages. One may assume that equivalent texts/utterances in two languages by means of translation generate equivalent meanings in their readers/hearers. This follows if we assume that meaning calculated from the linguistic input is solely objective in nature. However,…

We conducted a broad-coverage investigation of the effects of syntactic distance and word order on language processing against a dependency-annotated reading time corpus of English. A combined method of quantitative syntax and psycholinguistic analyses was adopted to yield converging evidence. It was found that (i) head-initial structures allow…

Data-driven learning uncontroversially plays a role in human language acquisition--how large a role is a matter of much debate. The success of artificial neural networks in NLP in recent years calls for a re-evaluation of our understanding of the possibilities for learning grammar from data alone. This dissertation argues the case for using…

Multilingualism presents both a challenge and an opportunity for Natural Language Processing, with code-switching representing a particularly interesting problem for computational models trained on monolingual datasets. In this paper, we explore how code-switched data affects the task of Machine Translation, a task which only recently has started…

Second language learners constitute a significant and expanding portion of the global population and there is a growing demand for tools that facilitate language learning and instruction across various levels and in different countries. The development of large language models (LLMs) has brought about a significant impact on the domains of natural…