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

Displaying 1 - 3 of 3
Filtering by

Clear all filters

187370-Thumbnail Image.png
Description
This project investigates the gleam-glum effect, a well-replicated phonetic emotion association in which words with the [i] vowel-sound (as in “gleam”) are judged more emotionally positive than words with the [Ʌ] vowel-sound (as in “glum”). The effect is observed across different modalities and languages and is moderated by mouth movements

This project investigates the gleam-glum effect, a well-replicated phonetic emotion association in which words with the [i] vowel-sound (as in “gleam”) are judged more emotionally positive than words with the [Ʌ] vowel-sound (as in “glum”). The effect is observed across different modalities and languages and is moderated by mouth movements relevant to word production. This research presents and tests an articulatory explanation for this association in three experiments. Experiment 1 supported the articulatory explanation by comparing recordings of 71 participants completing an emotional recall task and a word read-aloud task, showing that oral movements were more similar between positive emotional expressions and [i] articulation, and negative emotional expressions and [Ʌ] articulation. Experiment 2 partially supported the explanation with 98 YouTube recordings of natural speech. In Experiment 3, 149 participants judged emotions expressed by a speaker during [i] and [Ʌ] articulation. Contradicting the robust phonetic emotion association, participants judged more frequently that the speaker’s [Ʌ] articulatory movements were positive emotional expressions and [i] articulatory movements were negative emotional expressions. This is likely due to other visual emotional cues not related to oral movements and the order of word lists read by the speaker. Findings from the current project overall support an articulatory explanation for the gleam-glum effect, which has major implications for language and communication.
ContributorsYu, Shin-Phing (Author) / Mcbeath, Michael K (Thesis advisor) / Glenberg, Arthur M (Committee member) / Stone, Greg O (Committee member) / Coza, Aurel (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2023
165924-Thumbnail Image.png
Description

The importance of nonverbal communication has been well established through several theories including Albert Mehrabian's 7-38-55 rule that proposes the respective importance of semantics, tonality and facial expressions in communication. Although several studies have examined how emotions are expressed and preceived in communication, there is limited research investigating the relationshi

The importance of nonverbal communication has been well established through several theories including Albert Mehrabian's 7-38-55 rule that proposes the respective importance of semantics, tonality and facial expressions in communication. Although several studies have examined how emotions are expressed and preceived in communication, there is limited research investigating the relationship between how emotions are expressed through semantics and facial expressions. Using a facial expression analysis software to deconstruct facial expressions into features and a K-Nearest-Neighbor (KNN) machine learning classifier, we explored if facial expressions can be clustered based on semantics. Our findings indicate that facial expressions can be clustered based on semantics and that there is an inherent congruence between facial expressions and semantics. These results are novel and significant in the context of nonverbal communication and are applicable to several areas of research including the vast field of emotion AI and machine emotional communication.

ContributorsEverett, Lauren (Author) / Coza, Aurel (Thesis director) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2022-05
193402-Thumbnail Image.png
Description
The current program of work explores the potential efficacy of textured insoles for improving biomechanical performance and cognitive acuity during static and dynamic performance. Despite the vast conceptual framework supporting the versatile benefits of textured insoles, the current literature has primarily focused on incorporating this treatment during low-phase movements within

The current program of work explores the potential efficacy of textured insoles for improving biomechanical performance and cognitive acuity during static and dynamic performance. Despite the vast conceptual framework supporting the versatile benefits of textured insoles, the current literature has primarily focused on incorporating this treatment during low-phase movements within the diseased and elderly subset populations. The current study expands this research application by administering textured insole treatments to a healthy population during a physically demanding dynamic assessment and correlating the results to subjects' sensory perception. A convenience sample of 10 subjects was evaluated for their ability to maintain bilateral standing balance in a static condition and adapt to confined lane perturbations during standard track running. These evaluations were conducted under both control and textured insole conditions. Subjects also completed a visual analog scale test, rating the insole treatments based on surface roughness to establish a statistical relationship between individual perception and biomechanical performance. Results showed that textured insole treatments given intermediate ratings of perceived surface roughness significantly enhanced performance during bilateral standing balance and standard track running perturbation adaptation.
ContributorsBoll, Christopher Marly (Author) / Coza, Aurel (Thesis advisor) / Santello, Marco (Committee member) / Lockhart, Thurmon (Committee member) / Arizona State University (Publisher)
Created2024