Skip to main content

ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Date Range
2013 2019


The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters from human auditory models, such as auditory patterns and loudness, involves computationally intensive operations which can strain device resources. Hence, strategies for implementing computationally efficient human auditory models for loudness estimation have been studied in this thesis. Existing algorithms for reducing computations in auditory pattern and loudness estimation have been …

Contributors
Kalyanasundaram, Girish, Spanias, Andreas S, Tepedelenlioglu, Cihan, et al.
Created Date
2013

The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits that are easily identified or tracked. Indeed it has been shown that patients with enduring symptoms have difficulty describing their problems; therefore, there is an urgent need for a sensitive measure of brain activity that corresponds with higher order cognitive processing. The development of a neurophysiological metric that maps to …

Contributors
Utianski, Rene Lynn, Liss, Julie M, Berisha, Visar, et al.
Created Date
2014

Everyday speech communication typically takes place face-to-face. Accordingly, the task of perceiving speech is a multisensory phenomenon involving both auditory and visual information. The current investigation examines how visual information influences recognition of dysarthric speech. It also explores where the influence of visual information is dependent upon age. Forty adults participated in the study that measured intelligibility (percent words correct) of dysarthric speech in auditory versus audiovisual conditions. Participants were then separated into two groups: older adults (age range 47 to 68) and young adults (age range 19 to 36) to examine the influence of age. Findings revealed that all …

Contributors
Fall, Elizabeth, Liss, Julie, Berisha, Visar, et al.
Created Date
2014

As the number of devices with wireless capabilities and the proximity of these devices to each other increases, better ways to handle the interference they cause need to be explored. Also important is for these devices to keep up with the demand for data rates while not compromising on industry established expectations of power consumption and mobility. Current methods of distributing the spectrum among all participants are expected to not cope with the demand in a very near future. In this thesis, the effect of employing sophisticated multiple-input, multiple-output (MIMO) systems in this regard is explored. The efficacy of systems …

Contributors
Thontadarya, Niranjan, Bliss, Daniel W, Berisha, Visar, et al.
Created Date
2014

The problem of cooperative radar and communications signaling is investigated. Each system typically considers the other system a source of interference. Consequently, the tradition is to have them operate in orthogonal frequency bands. By considering the radar and communications operations to be a single joint system, performance bounds on a receiver that observes communications and radar return in the same frequency allocation are derived. Bounds in performance of the joint system is measured in terms of data information rate for communications and radar estimation information rate for the radar. Inner bounds on performance are constructed. Dissertation/Thesis

Contributors
Chiriyath, Alex Rajan, Bliss, Daniel W, Kosut, Oliver, et al.
Created Date
2014

Head movement is known to have the benefit of improving the accuracy of sound localization for humans and animals. Marmoset is a small bodied New World monkey species and it has become an emerging model for studying the auditory functions. This thesis aims to detect the horizontal and vertical rotation of head movement in marmoset monkeys. Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and …

Contributors
Simhadri, Sravanthi, Zhou, Yi, Turaga, Pavan, et al.
Created Date
2014

The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied subspace in a multi-user environment from multiple temporal samples of the signal received at a single antenna. These estimators enable identification of resources, such as the orthogonal complement of the occupied subspace, that may be exploitable by an opportunistic user. This concept is supported by simulations showing the estimation of the number of users in a …

Contributors
Beaudet, Kaitlyn, Cochran, Douglas, Turaga, Pavan, et al.
Created Date
2014

This work considers the problem of multiple detection and tracking in two complex time-varying environments, urban terrain and underwater. Tracking multiple radar targets in urban environments is rst investigated by exploiting multipath signal returns, wideband underwater acoustic (UWA) communications channels are estimated using adaptive learning methods, and multiple UWA communications users are detected by designing the transmit signal to match the environment. For the urban environment, a multi-target tracking algorithm is proposed that integrates multipath-to-measurement association and the probability hypothesis density method implemented using particle filtering. The algorithm is designed to track an unknown time-varying number of targets by extracting …

Contributors
Zhou, Meng, Papandreou-Suppappola, Antonia, Tepedelenlioglu, Cihan, et al.
Created Date
2014

The present study describes audiovisual sentence recognition in normal hearing listeners, bimodal cochlear implant (CI) listeners and bilateral CI listeners. This study explores a new set of sentences (the AzAV sentences) that were created to have equal auditory intelligibility and equal gain from visual information. The aims of Experiment I were to (i) compare the lip reading difficulty of the AzAV sentences to that of other sentence materials, (ii) compare the speech-reading ability of CI listeners to that of normal-hearing listeners and (iii) assess the gain in speech understanding when listeners have both auditory and visual information from easy-to-lip-read and …

Contributors
Wang, Shuai, Dorman, Michael, Berisha, Visar, et al.
Created Date
2015

Audio signals, such as speech and ambient sounds convey rich information pertaining to a user’s activity, mood or intent. Enabling machines to understand this contextual information is necessary to bridge the gap in human-machine interaction. This is challenging due to its subjective nature, hence, requiring sophisticated techniques. This dissertation presents a set of computational methods, that generalize well across different conditions, for speech-based applications involving emotion recognition and keyword detection, and ambient sounds-based applications such as lifelogging. The expression and perception of emotions varies across speakers and cultures, thus, determining features and classification methods that generalize well to different conditions …

Contributors
Shah, Mohit, Spanias, Andreas, Chakrabarti, Chaitali, et al.
Created Date
2015