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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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 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
Description
Contact tracing has been shown to be effective in limiting the rate of spread of infectious diseases like COVID-19. Several solutions based on the exchange of random, anonymous tokens between users’ mobile devices via Bluetooth, or using users’ location traces have been proposed and deployed. These solutions require the user device to download the tokens (or traces) of infected users from the server. The user tokens are matched with infected users’ tokens to determine an exposure event. These solutions are vulnerable to a range of security and privacy issues, and require large downloads, thus warranting the need for an efficient protocol with strong privacy guarantees. Moreover, these solutions are based solely on proximity between user devices, while COVID-19 can spread from common surfaces as well. Knowledge of areas with a large number of visits by infected users (hotspots) can help inform users to avoid those areas and thereby reduce surface transmission. This thesis proposes a strong secure system for contact tracing and hotspots histogram computation. The contact tracing protocol uses a combination of Bluetooth Low Energy and Global Positioning System (GPS) location data. A novel and deployment-friendly Delegated Private Set Intersection Cardinality protocol is proposed for efficient and secure server aided matching of tokens. Secure aggregation techniques are used to allow the server to learn areas of high risk from location traces of diagnosed users, without revealing any individual user’s location history.
ContributorsSurana, Chetan (Author) / Trieu, Ni (Thesis advisor) / Sankar, Lalitha (Committee member) / Berisha, Visar (Committee member) / Zhao, Ming (Committee member) / Arizona State University (Publisher)
Created2021