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Articles 1 - 11 of 11
Full-Text Articles in Computational Linguistics
Data-Driven Neuroanatomical Subtypes In Various Stages Of Schizophrenia: Linking Cortical Thickness, Glutamate, And Language Functioning, Liangbing Liang
Data-Driven Neuroanatomical Subtypes In Various Stages Of Schizophrenia: Linking Cortical Thickness, Glutamate, And Language Functioning, Liangbing Liang
Electronic Thesis and Dissertation Repository
The considerable variation in the spatial distribution of cortical thickness changes has been used to parse heterogeneity in schizophrenia. We aimed to recover a ‘cortical impoverishment’ subgroup with widespread cortical thinning. We applied hierarchical cluster analysis to cortical thickness data of three datasets in different stages of psychosis and studied the cognitive, functional, neurochemical, language and symptom profiles of the observed subgroups. Our consensus-based clustering procedure consistently produced a subgroup characterized by significantly lower cortical thickness. This ‘cortical impoverishment’ subgroup was associated with a higher symptom burden in a clinically stable sample and higher glutamate levels with language impairments in …
Linguistic Abstractions In Children’S Very Early Utterances, Qihui Xu
Linguistic Abstractions In Children’S Very Early Utterances, Qihui Xu
Dissertations, Theses, and Capstone Projects
How early do children produce multiword utterances? Do children's early utterances reflect abstract syntactic knowledge or are they the result of data-driven learning? We examine this issue through corpus analysis, computational modeling, and adult simulation experiments. Chapter 1 investigates when children start producing multiword utterances; we use corpora to establish the development of multiword utterances and a probabilistic computational model to account for the quantitative change of early multiword utterances. We find that multiword utterances of different lengths appear early in acquisition and increase together, and the length growth pattern can be viewed as a probabilistic and dynamic process.
Chapter …
Predicting Stress In Russian Using Modern Machine-Learning Tools, John Schriner
Predicting Stress In Russian Using Modern Machine-Learning Tools, John Schriner
Dissertations, Theses, and Capstone Projects
In the Russian language, stress on a word is determined via often complex patterns and rules. In this paper, after examining nearly a century of research in stress rules and methods in Russian, we turn to see if modern machine learning tools can aid in predicting stress. Using A.A. Zaliznyak’s dictionary grammar and over 300,000 word forms, we derived stress codes to aid in predicting which syllable primary stress falls on. We trained an LSTM neural network on the data and conducted eight experiments with added features such as lemma, part of speech, and morphology. While the model performed better …
Towards Explaining Variation In Entrainment, Andreas Weise
Towards Explaining Variation In Entrainment, Andreas Weise
Dissertations, Theses, and Capstone Projects
Entrainment refers to the tendency of human speakers to adapt to their interlocutors to become more similar to them. This affects various dimensions and occurs in many contexts, allowing for rich applications in human-computer interaction. However, it is not exhibited by every speaker in every conversation but varies widely across features, speakers, and contexts, hindering broad application. This variation, whose guiding principles are poorly understood even after decades of entrainment research, is the subject of this thesis. We begin with a comprehensive literature review that serves as the foundation of our own work and provides a reference to guide future …
From Sesame Street To Beyond: Multi-Domain Discourse Relation Classification With Pretrained Bert, Isaac R. Raff
From Sesame Street To Beyond: Multi-Domain Discourse Relation Classification With Pretrained Bert, Isaac R. Raff
Dissertations, Theses, and Capstone Projects
Research efforts in transfer learning have gained massive popularity in recent years. Pretrained language models have demonstrated the most successful results in producing high quality neural networks capable of quality inference after training across domains via transfer learning. This study expands on the domain transfer introduced in \cite{ferracane-etal-2019-news} exploring neural methods for transfer learning of discourse parsing between a news source domain and a medical target domain. \cite{ferracane-etal-2019-news} specifically discuss transfer learning from news articles to PubMed medical journal articles. Experiments in transfer learning in the current work expand to include three domains: Wall Street Journal articles previously annotated with …
Corrective Feedback Timing In Kanji Writing Instruction Apps, Phoenix Mulgrew
Corrective Feedback Timing In Kanji Writing Instruction Apps, Phoenix Mulgrew
Honors Theses
The focus of this research paper is to determine the correct time to provide corrective feedback to people who are learning how to write Japanese kanji. To do this, we developed a system that is able to recognize Japanese kanji that is handwritten onto an iPad screen and check for errors such as wrong stroke order. Previous research has achieved success in developing similar systems, but this project is unique because the research question involves the timing of corrective feedback. In particular, we are looking at whether immediate or delayed corrective feedback results in better learning.
A Machine Learning Approach To Text-Based Sarcasm Detection, Lara I. Novic
A Machine Learning Approach To Text-Based Sarcasm Detection, Lara I. Novic
Dissertations, Theses, and Capstone Projects
Sarcasm and indirect language are commonplace for humans to produce and recognize but difficult for machines to detect. While artificial intelligence can accurately analyze sentiment and emotion in speech and text, it may struggle with insincere and sardonic content, although it is possible to train a machine to identify uttered and written sarcasm. This paper aims to detect sarcasm using logistic regression and a support vector machine (SVM) and compare their results to a baseline.
The models are trained on headlines from a Kaggle dataset containing headlines from the satirical news website The Onion and serious news website Huffpost (formerly …
Covert Determiners In Appalachian English Narrative Declarative Sentences, William Oliver
Covert Determiners In Appalachian English Narrative Declarative Sentences, William Oliver
Dissertations, Theses, and Capstone Projects
In this thesis, I explore the syntax and semantics of covert determiners (Ds) in matrix subject determiner phrases (DPs) with definite specific interpretations. To conduct my investigation, I used the Audio-Aligned and Parsed Corpus of Appalachian English (AAPCAppE), a million-word Penn Treebank corpus, and the software CorpusSearch, a Java program that searches Penn Treebank corpora. My research shows that Appalachian English contains a linguistic phenomenon where speakers drop the D, replacing overt Ds with covert Ds, in definite specific DPs. For example, where Standard English speakers say The doctor came by horseback, Appalachian speakers may use a covert D …
Metaphor Detection In Poems In Misurata Arabic Sub-Dialect : An Lstm Model, Azza Abugharsa
Metaphor Detection In Poems In Misurata Arabic Sub-Dialect : An Lstm Model, Azza Abugharsa
Theses, Dissertations and Culminating Projects
Natural Language Processing (NLP) in Arabic is witnessing an increasing interest in investigating different topics in the field. One of the topics that have drawn attention is the automatic processing of Arabic figurative language. The focus in previous projects is on detecting and interpreting metaphors in comments from social media as well as phrases and/or headlines from news articles. The current project focuses on metaphor detection in poems written in the Misurata Arabic sub-dialect spoken in Misurata, located in the North African region. The dataset is initially annotated by a group of linguists, and their annotation is treated as the …
“I Can See The Forest For The Trees”: Examining Personality Traits With Trasformers, Alexander Moore
“I Can See The Forest For The Trees”: Examining Personality Traits With Trasformers, Alexander Moore
All Dissertations
Our understanding of Personality and its structure is rooted in linguistic studies operating under the assumptions made by the Lexical Hypothesis: personality characteristics that are important to a group of people will at some point be codified in their language, with the number of encoded representations of a personality characteristic indicating their importance. Qualitative and quantitative efforts in the dimension reduction of our lexicon throughout the mid-20th century have played a vital role in the field’s eventual arrival at the widely accepted Five Factor Model (FFM). However, there are a number of presently unresolved conflicts regarding the breadth and …
Prácticas Comunicativas Digitales Y Construcción De Subjetividades: El Uso Del Podcast En La Escuela, María Isabel Guevara Rodríguez
Prácticas Comunicativas Digitales Y Construcción De Subjetividades: El Uso Del Podcast En La Escuela, María Isabel Guevara Rodríguez
Doctorado en Educación y Sociedad
No abstract provided.