Computational Linguistics Commons^™

Genderlects In Social Media, Alina Korovatskaya

Dissertations, Theses, and Capstone Projects

Many studies have found significant differences in ways men and women use language; some argue that these differences occur as a result of culture differences, and others suggest that they are influenced by differences in social status and power between the genders. However, some of the major studies were concluded decades ago and do not reflect changes in gender relations in recent years. In this study, we analyze modern conversations using two social media platforms, Twitter and Reddit, to determine whether substantial differences between men and women’s use of language were preserved between the genders.

Doing Away With Defaults: Motivation For A Gradient Parameter Space, Katherine Howitt

Dissertations, Theses, and Capstone Projects

In this thesis, I propose a reconceptualization of the traditional syntactic parameter space of the principles and parameters framework (Chomsky, 1981). In lieu of binary parameter settings, parameter values exist on a gradient plane where a learner’s knowledge of their language is encoded in their confidence that a particular parametric target value, and thus grammatical construction of an encountered sentence, is likely to be licensed by their target grammar. First, I discuss other learnability models in the classic parameter space which lack either psychological plausibility, theoretical consistency, or some combination of the two. Then, I argue for the Gradient Parameter …

English Wordnet Taxonomic Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Conference papers

This is a resource description paper that describes the creation and properties of a set of pseudo-corpora generated artificially from a random walk over the English WordNet taxonomy. Our WordNet taxonomic random walk implementation allows the exploration of different random walk hyperparameters and the generation of a variety of different pseudo-corpora. We find that different combinations of the walk’s hyperparameters result in varying statistical properties of the generated pseudo-corpora. We have published a total of 81 pseudo-corpora that we have used in our previous research, but have not exhausted all possible combinations of hyperparameters, which is why we have also …

Chaprates, Brinly Xavier, Micole Amanda Marietta, Nidhi Vedantam

Student Scholar Symposium Abstracts and Posters

On the Chapman campus, through taking and choosing various classes, there is a significant need for communication and feedback between students and peers, professors, tutors, and study groups. With this, we wanted to create an application that enables users from various majors to not only easily and effectively communicate with various people in their field, but one that also enables them to give and receive feedback on various classes through a rating system. We believe that the application will aid students in a myriad of specific ways, including being involved in study groups and getting tutoring help, determining which classes …

Computational Approaches To The Syntax–Prosody Interface: Using Prosody To Improve Parsing, Hussein M. Ghaly

Dissertations, Theses, and Capstone Projects

Prosody has strong ties with syntax, since prosody can be used to resolve some syntactic ambiguities. Syntactic ambiguities have been shown to negatively impact automatic syntactic parsing, hence there is reason to believe that prosodic information can help improve parsing. This dissertation considers a number of approaches that aim to computationally examine the relationship between prosody and syntax of natural languages, while also addressing the role of syntactic phrase length, with the ultimate goal of using prosody to improve parsing.

Chapter 2 examines the effect of syntactic phrase length on prosody in double center embedded sentences in French. Data collected …

Phonologically-Informed Speech Coding For Automatic Speech Recognition-Based Foreign Language Pronunciation Training, Anthony J. Vicario

Dissertations, Theses, and Capstone Projects

Automatic speech recognition (ASR) and computer-assisted pronunciation training (CAPT) systems used in foreign-language educational contexts are often not developed with the specific task of second-language acquisition in mind. Systems that are built for this task are often excessively targeted to one native language (L1) or a single phonemic contrast and are therefore burdensome to train. Current algorithms have been shown to provide erroneous feedback to learners and show inconsistencies between human and computer perception. These discrepancies have thus far hindered more extensive application of ASR in educational systems.

This thesis reviews the computational models of the human perception of American …

Ghost Peppers: Using Ensemble Models To Detect Professor Attractiveness Commentary On Ratemyprofessors.Com, Angie Waller

Dissertations, Theses, and Capstone Projects

In June 2018, RateMyProfessors.com (RMP), a popular website for students to leave professor reviews, removed a controversial feature known as the “chili pepper” which allowed students to rate their professors as “hot” or “not hot.” Though past research has rigorously analyzed the correlation of the chili pepper with higher ratings in other categories (Felton, Mitchell, and Stinson, 2004; Felton et al., 2008), none has measured the effect of the removal of the chili pepper on the text content submitted by students. While it is a positive step that the chili pepper has been removed, text commentary on teacher attractiveness persists …

You Don’T Say... Linguistic Features In Sarcasm Detection, Martina Ducret, Lauren Kruse, Carlos Martinez, Anna Feldman, Jing Peng

Department of Computer Science Faculty Scholarship and Creative Works

We explore linguistic features that contribute to sarcasm detection. The linguistic features that we investigate are a combination of text and word complexity, stylistic and psychological features. We experiment with sarcastic tweets with and without context. The results of our experiments indicate that contextual information is crucial for sarcasm prediction. One important observation is that sarcastic tweets are typically incongruent with their context in terms of sentiment or emotional load.

Pmkns For Pie: Parsed Morphological Katr Networks Of Sanskrit For Proto-Indo-European, Ryan Mark Mcdonald

Theses and Dissertations--Linguistics

In this thesis, I construct two computational networks for Sanskrit to test theories of nominal accentuation as a way of examining the simplicity of each theory. I will be examining the Paradigmatic Approach and the Compositional Approach to nominal accentuation. For the Paradigmatic Approach, nominals are categorized into mobile and static categories based on how the accent appears in the paradigm (Fortson 2010). For the Compositional Approach, accent mobility is a result of the combination of morphemes and their inherent accent states (Kirparsky 2010). To construct these networks, I use the KATR extension to the DATR language for lexical knowledge …

The Stained Glass Of Knowledge: On Understanding Novice Mental Models Of Computing, Briana Christina Bettin

Dissertations, Master's Theses and Master's Reports

Learning to program can be a novel experience. The rigidity of programming can be at odds with beginning programmer's existing perceptions, and the concepts can feel entirely unfamiliar. These observations motivated this research, which explores two major questions: What factors influence how novices learn programming? and How can analogy by more appropriately leveraged in programming education?

This dissertation investigates the factors influencing novice programming through multiple methods. The CS1 classroom is observed as a "whole system", with consideration to the factors present in it that can influence the learning process. Learning's cognitive processes are elaborated to ground exploration into specifically …

Scholarly Communication And Documentary Fragmentations In The Public Space: A Functional Citation Study, Fidelia Ibekwe, Lucie Loubère

Proceedings from the Document Academy

This paper studies how academic content published in Open Edition.org, an online publication platform in the Social Sciences and Humanities is re-appropriated by members of the public. Our research is therefore concerned with the public appropriation of science and Open science. After extracting the contexts of citation of these content and mapping them, we propose a typology of citation functions as well as of citers (their origins and types). Our preliminary results indicated that academic literature is repurposed and cited by members of the public mainly as scientific warrant (support for their argumentation). We also found that academic content is …

Size Matters: The Impact Of Training Size In Taxonomically-Enriched Word Embeddings, Alfredo Maldonado, Filip Klubicka, John D. Kelleher

Articles

Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel in capturing thematic similarity (“topical relatedness”) on word pairs such as ‘coffee’ and ‘cup’ or ’bus’ and ‘road’. However, they are less successful on pairs showing taxonomic similarity, like ‘cup’ and ‘mug’ (near synonyms) or ‘bus’ and ‘train’ (types of public transport). Moreover, purely taxonomy-based embeddings (e.g. those trained on a random-walk of WordNet’s structure) outperform natural-corpus embeddings in taxonomic similarity but underperform them in thematic similarity. Previous work suggests that performance gains in both types of similarity can be achieved by enriching natural-corpus embeddings with …

Demographic Factors As Domains For Adaptation In Linguistic Preprocessing, Sara Morini

Dissertations, Theses, and Capstone Projects

Classic natural language processing resources such as the Penn Treebank (Marcus et al. 1993) have long been used both as evaluation data for many linguistic tasks and as training data for a variety of off-the-shelf language processing tools. Recent work has highlighted a gender imbalance in the authors of this text data (Garimella et al. 2019) and hypothesized that tools created with such resources will privilege users from particular demographic groups (Hovy and Søgaard 2015). Domain adaptation is typically employed as a strategy in machine learning to adjust models trained and evaluated with data from different genres. However, the present …

Do It Like A Syntactician: Using Binary Gramaticality Judgements To Train Sentence Encoders And Assess Their Sensitivity To Syntactic Structure, Pablo Gonzalez Martinez

Dissertations, Theses, and Capstone Projects

The binary nature of grammaticality judgments and their use to access the structure of syntax are a staple of modern linguistics. However, computational models of natural language rarely make use of grammaticality in their training or application. Furthermore, developments in modern neural NLP have produced a myriad of methods that push the baselines in many complex tasks, but those methods are typically not evaluated from a linguistic perspective. In this dissertation I use grammaticality judgements with artificially generated ungrammatical sentences to assess the performance of several neural encoders and propose them as a suitable training target to make models learn …

Synthetic, Yet Natural: Properties Of Wordnet Random Walk Corpora And The Impact Of Rare Words On Embedding Performance, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Conference papers

Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources is an open challenge. One approach is to use a random walk over a knowledge graph to generate a pseudo-corpus and use this corpus to train embeddings. However, the effect of the shape of the knowledge graph on the generated pseudo-corpora, and on the resulting word embeddings, has not been studied. To explore this, we use English WordNet, constrained to the taxonomic (tree-like) portion of the graph, as a case study. We investigate the properties of the generated pseudo-corpora, and their impact on the resulting embeddings. We find …

Beneath The Surface Of Talking About Physicians: A Statistical Model Of Language For Patient Experience Comments, Taylor Turpen, Lea Matthews Md, Senem Guney Phd, Cpxp

Patient Experience Journal

This study applies natural language processing (NLP) techniques to patient experience comments. Our goal was to examine the language describing care experiences with two groups of physicians: those with scores in the top 100 and those with scores in the bottom 100 among all physicians (n=498) who received scores from patient satisfaction surveys. Our analysis showed a statistically significant difference in the language used to describe care experiences with these two distinct groups of physicians. This analysis illustrates how to apply NLP techniques in categorizing and building a statistical model for language use in order to identify meaningful language and …

The Design And Implementation Of Aida: Ancient Inscription Database And Analytics System, M. Parvez Rashid

School of Computing: Dissertations, Theses, and Student Research

AIDA, the Ancient Inscription Database and Analytic system can be used to translate and analyze ancient Minoan language. The AIDA system currently stores three types of ancient Minoan inscriptions: Linear A, Cretan Hieroglyph and Phaistos Disk inscriptions. In addition, AIDA provides candidate syllabic values and translations of Minoan words and inscriptions into English. The AIDA system allows the users to change these candidate phonetic assignments to the Linear A, Cretan Hieroglyph and Phaistos symbols. Hence the AIDA system provides for various scholars not only a convenient online resource to browse Minoan inscriptions but also provides an analysis tool to explore …

Analyzing Prosody With Legendre Polynomial Coefficients, Rachel Rakov

Dissertations, Theses, and Capstone Projects

This investigation demonstrates the effectiveness of Legendre polynomial coefficients representing prosodic contours within the context of two different tasks: nativeness classification and sarcasm detection. By making use of accurate representations of prosodic contours to answer fundamental linguistic questions, we contribute significantly to the body of research focused on analyzing prosody in linguistics as well as modeling prosody for machine learning tasks. Using Legendre polynomial coefficient representations of prosodic contours, we answer prosodic questions about differences in prosody between native English speakers and non-native English speakers whose first language is Mandarin. We also learn more about prosodic qualities of sarcastic speech. …

The Perception Of Mandarin Tones In "Bubble" Noise By Native And L2 Listeners, Mengxuan Zhao

Dissertations, Theses, and Capstone Projects

Previous studies have revealed the complexity of Mandarin Tones. For example, similarities in the pitch contours of tones 2 and 3 and tones 3 and 4 cause confusion for listeners. The realization of a tone's contour is highly dependent on its context, especially the preceding pitch. This is known as the coarticulation effect. Researchers have demonstrated the robustness of tone perception by both native and non-native listeners, even with incomplete acoustic information or in noisy environment. However, non-native listeners were observed to behave differently from native listeners in their use of contextual information. For example, the disagreement between the end …

Quantifying Coherence In A Transdiagnostic Sample: A Methodological Investigation Of Computationally-Derived Coherence Using Ambulatory Assessment, Taylor L. Fedechko

LSU Master's Theses

Schizophrenia is a clinical diagnosis assigned to individuals that experience positive (e.g., hallucinations and delusions), negative (e.g., blunted affect), and disorganized (e.g., incoherent speech) symptoms. One particularly disabling symptom is incoherence, which is defined as the meaning-based relationship between ideas. This symptom can drastically affect an individual’s quality of life by affecting areas such as social and occupational functioning. Currently, the mechanism behind this symptom is unknown and requires further study. One way to examine incoherence is to understand its level of expression in other clinical populations. With the advent of computationally-derived natural language processing (NLP), coherence can be quantified …

Obfuscating Authorship: Results Of A User Study On Nondescript, A Digital Privacy Tool, Robin Camille Davis

Publications and Research

For those who write anonymously, particularly for safety reasons, authorship attribution poses a threat. Nondescript, my web app, guides writers in achieving stylometric obfuscation in order to preserve anonymity. The app runs simulations of authorship attribution scenarios by analyzing the user’s linguistic features. In this paper, I will describe the conception of the Nondescript app; discuss related work; and present the results of a user study. Most users in the study were able to anonymize their writing in at least 5 out of 10 authorship attribution scenarios. Users rated the anonymization process an average of 3.6 out of 5 in …

Generative Adversarial Networks And Word Embeddings For Natural Language Generation, Robert D. Schultz Jr

Dissertations, Theses, and Capstone Projects

We explore using image generation techniques to generate natural language. Generative Adversarial Networks (GANs), normally used for image generation, were used for this task. To avoid using discrete data such as one-hot encoded vectors, with dimensions corresponding to vocabulary size, we instead use word embeddings as training data. The main motivation for this is the fact that a sentence translated into a sequence of word embeddings (a “word matrix”) is an analogue to a matrix of pixel values in an image. These word matrices can then be used to train a generative adversarial model. The output of the model’s generator …

Leveraging Nlp And Social Network Analytic Techniques To Detect Censored Keywords: System Design And Experiments, Christopher S. Leberknight, Anna Feldman

Department of Computer Science Faculty Scholarship and Creative Works

Internet regulation in the form of online censorship and Internet shutdowns have been increasing over recent years. This paper presents a natural language processing (NLP) application for performing cross country probing that conceals the exact location of the originating request. A detailed discussion of the application aims to stimulate further investigation into new methods for measuring and quantifying Internet censorship practices around the world. In addition, results from two experiments involving search engine queries of banned keywords demonstrates censorship practices vary across different search engines. These results suggest opportunities for developing circumvention technologies that enable open and free access to …

Application Of Boolean Logic To Natural Language Complexity In Political Discourse, Austin Taing

Theses and Dissertations--Computer Science

Press releases serve as a major influence on public opinion of a politician, since they are a primary means of communicating with the public and directing discussion. Thus, the public’s ability to digest them is an important factor for politicians to consider. This study employs several well-studied measures of linguistic complexity and proposes a new one to examine whether politicians change their language to become more or less difficult to parse in different situations. This study uses 27,500 press releases from the US Senate between 2004–2008 and examines election cycles and natural disasters, namely hurricanes, as situations where politicians’ language …

Non-Manual Articulators In Irish Sign Language Verbs: An Analysis With Data Mining Association Rules, Robert G. Smith, Markus Hofmann

Conference Papers

The Signs of Ireland (SOI) corpus (Leeson et al., 2006) deploys a complex multi-tiered temporal data structure. The process of manually analyzing such data is laborious, cannot eliminate bias and often, important patterns can go completely unnoticed. In addition to this, as a result of the complex nature of grammatical structures contained in the corpus, identifying complex linguistic associations or patterns across tiers is simply too intricate a task for a human to carry out in an acceptable timeframe. This work explores the application of data mining techniques on a set of multi-tiered temporal data from the SOI corpus. Building …

Recursive Neural Networks For Semantic Sentence Representation, Liam S. Geron

Dissertations, Theses, and Capstone Projects

Semantic representation has a rich history rife with both complex linguistic theory and computational models. Though this history stretches back almost 50 years (Salton, 1971), recently the field has undergone an unexpected shift in paradigm thanks to the work of Mikolov et al., 2013(a & b) which has proven that vector-space semantic models can capture large amounts of semantic information. As of yet, these semantic representations are computed at the word level, and finding a semantic representation of a phrase is a much more difficult challenge. Mikolov et al., 2013(a&b) proved that their word vectors can be composed arithmetically to …

Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Publications

Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers. …

Perception & Perspective: An Analysis Of Discourse And Situational Factors In Reference Frame Selection, Robert J. Ross, Kavita E. Thomas

Conference papers

To integrate perception into dialogue, it is necessary to bind spatial language descriptions to reference frame use. To this end, we present an analysis of discourse and situational factors that may influence reference frame choice in dialogues. We show that factors including spatial orientation, task, self and other alignment, and dyad have an influence on reference frame use. We further show that a computational model to estimate reference frame based on these features provides results greater than both random and greedy reference frame selection strategies.

Nevertheless, She Persisted: A Linguistic Analysis Of The Speech Of Elizabeth Warren, 2007-2017, Matthew Jennings

Undergraduate Honors Theses

A breakout star among American progressives in the recent past, Elizabeth Warren has quickly gone from a law professor to a leading figure in Democratic politics. This paper analyzes Warren’s speech from before her time as a political figure to the present using the quantitative textual methodology established by Jones (2016) in order to see if Warren’s speech supports Jones’s assertion that masculine speech is the language of power. Ratios of feminine to masculine markers ultimately indicate that despite her increasing political sway, Warren’s speech becomes increasingly feminine instead. However, despite associations of feminine speech with weakness, Warren’s speech scores …

Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales

Dissertations, Theses, and Capstone Projects

Depression is a serious illness that affects a large portion of the world’s population. Given the large effect it has on society, it is evident that depression is a serious health issue. This thesis evaluates, at length, how technology may aid in assessing depression. We present an in-depth investigation of features and fusion techniques for depression detection systems. We also present OpenMM: a novel tool for multimodal feature extraction. Lastly, we present novel techniques for multimodal fusion. The contributions of this work add considerably to our knowledge of depression detection systems and have the potential to improve future systems by …