Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Glottal fry in college aged females: an entrainment phenomenon?

Description
Glottal fry is a vocal register characterized by low frequency and increased signal perturbation, and is perceptually identified by its popping, creaky quality. Recently, the use of the glottal fry vocal register has received growing awareness and attention in popular culture and media in the United States. The creaky quality…

Glottal fry is a vocal register characterized by low frequency and increased signal perturbation, and is perceptually identified by its popping, creaky quality. Recently, the use of the glottal fry vocal register has received growing awareness and attention in popular culture and media in the United States. The creaky quality that was originally associated with vocal pathologies is indeed becoming “trendy,” particularly among young women across the United States. But while existing studies have defined, quantified, and attempted to explain the use of glottal fry in conversational speech, there is currently no explanation for the increasing prevalence of the use of glottal fry amongst American women. This thesis, however, proposes that conversational entrainment—a communication phenomenon which describes the propensity to modify one’s behavior to align more closely with one’s communication partner—may provide a theoretical framework to explain the growing trend in the use of glottal fry amongst college-aged women in the United States. Female participants (n = 30) between the ages of 18 and 29 years (M = 20.6, SD = 2.95) had conversations with two conversation partners, one who used quantifiably more glottal fry than the other. The study utilized perceptual and quantifiable acoustic information to address the following key question: Does the amount of habitual glottal fry in a conversational partner influence one’s use of glottal fry in their own speech? Results yielded the following two findings: (1) according to perceptual annotations, the participants used a greater amount of glottal fry when speaking with the Fry conversation partner than with the Non Fry partner, (2) statistically significant differences were found in the acoustics of the participants’ vocal qualities based on conversation partner. While the current study demonstrates that young women are indeed speaking in glottal fry in everyday conversations, and that its use can be attributed in part to conversational entrainment, we still lack a clear explanation of the deeper motivations for women to speak in a lower vocal register. The current study opens avenues for continued analysis of the sociolinguistic functions of the glottal fry register.
ContributorsDelfino, Christine R (Author) / Liss, Julie M (Thesis advisor) / Borrie, Stephanie A (Thesis advisor) / Azuma, Tamiko (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2015
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Characterizing the Performance of Machine Learning Algorithms: A Study and Novel Techniques

Description

Classification in machine learning is quite crucial to solve many problems that the world is presented with today. Therefore, it is key to understand one’s problem and develop an efficient model to achieve a solution. One technique to achieve greater model selection and thus further ease in problem solving is…

Classification in machine learning is quite crucial to solve many problems that the world is presented with today. Therefore, it is key to understand one’s problem and develop an efficient model to achieve a solution. One technique to achieve greater model selection and thus further ease in problem solving is estimation of the Bayes Error Rate. This paper provides the development and analysis of two methods used to estimate the Bayes Error Rate on a given set of data to evaluate performance. The first method takes a “global” approach, looking at the data as a whole, and the second is more “local”—partitioning the data at the outset and then building up to a Bayes Error Estimation of the whole. It is found that one of the methods provides an accurate estimation of the true Bayes Error Rate when the dataset is at high dimension, while the other method provides accurate estimation at large sample size. This second conclusion, in particular, can have significant ramifications on “big data” problems, as one would be able to clarify the distribution with an accurate estimation of the Bayes Error Rate by using this method.
ContributorsLattus, Robert (Author) / Dasarathy, Gautam (Thesis director) / Berisha, Visar (Committee member) / Turaga, Pavan (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2021-12