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.
Displaying 1 - 5 of 5
Filtering by
- Creators: Zhou, Yi
- Creators: Krantsevich, Chelsea
Description
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 closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses 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 closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses in marmoset monkeys.
ContributorsSimhadri, Sravanthi (Author) / Zhou, Yi (Thesis advisor) / Turaga, Pavan (Thesis advisor) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014
Description
Callithrix jacchus, also known as a common marmoset, is native to the new world. These marmosets possess a wide range of vocal repertoire that is interesting to observe for the purpose of understanding their group communication and their fight or flight responses to the environment around them. In this project, I am continuing with the project that a previous student, Jasmin, had done to find more data for her study. For the most part, my project entailed recording and labeling the marmoset’s calls into different types.
ContributorsTran, Anh (Author) / Zhou, Yi (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This dissertation explores applications of machine learning methods in service of the design of screening tests, which are ubiquitous in applications from social work, to criminology, to healthcare. In the first part, a novel Bayesian decision theory framework is presented for designing tree-based adaptive tests. On an application to youth delinquency in Honduras, the method produces a 15-item instrument that is almost as accurate as a full-length 150+ item test. The framework includes specific considerations for the context in which the test will be administered, and provides uncertainty quantification around the trade-offs of shortening lengthy tests. In the second part, classification complexity is explored via theoretical and empirical results from statistical learning theory, information theory, and empirical data complexity measures. A simulation study that explicitly controls two key aspects of classification complexity is performed to relate the theoretical and empirical approaches. Throughout, a unified language and notation that formalizes classification complexity is developed; this same notation is used in subsequent chapters to discuss classification complexity in the context of a speech-based screening test. In the final part, the relative merits of task and feature engineering when designing a speech-based cognitive screening test are explored. Through an extensive classification analysis on a clinical speech dataset from patients with normal cognition and Alzheimer’s disease, the speech elicitation task is shown to have a large impact on test accuracy; carefully performed task and feature engineering are required for best results. A new framework for objectively quantifying speech elicitation tasks is introduced, and two methods are proposed for automatically extracting insights into the aspects of the speech elicitation task that are driving classification performance. The dissertation closes with recommendations for how to evaluate the obtained insights and use them to guide future design of speech-based screening tests.
ContributorsKrantsevich, Chelsea (Author) / Hahn, P. Richard (Thesis advisor) / Berisha, Visar (Committee member) / Lopes, Hedibert (Committee member) / Renaut, Rosemary (Committee member) / Zheng, Yi (Committee member) / Arizona State University (Publisher)
Created2023
Description
The marmoset monkey (Callithrix jacchus) is a new-world primate species native to South America rainforests. Because they rely on vocal communication to navigate and survive, marmosets have evolved as a promising primate model to study vocal production, perception, cognition, and social interactions. The purpose of this project is to provide an initial assessment on the vocal repertoire of a marmoset colony raised at Arizona State University and call types they use in different social conditions. The vocal production of a colony of 16 marmoset monkeys was recorded in 3 different conditions with three repeats of each condition. The positive condition involves a caretaker distributing food, the negative condition involves an experimenter taking a marmoset out of his cage to a different room, and the control condition is the normal state of the colony with no human interference. A total of 5396 samples of calls were collected during a total of 256 minutes of audio recordings. Call types were analyzed in semi-automated computer programs developed in the Laboratory of Auditory Computation and Neurophysiology. A total of 5 major call types were identified and their variants in different social conditions were analyzed. The results showed that the total number of calls and the type of calls made differed in the three social conditions, suggesting that monkey vocalization signals and depends on the social context.
ContributorsFernandez, Jessmin Natalie (Author) / Zhou, Yi (Thesis director) / Berisha, Visar (Committee member) / School of International Letters and Cultures (Contributor) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The poor spectral and temporal resolution of cochlear implants (CIs) limit their users’ music enjoyment. Remixing music by boosting vocals while attenuating spectrally complex instruments has been shown to benefit music enjoyment of postlingually deaf CI users. However, the effectiveness of music remixing in prelingually deaf CI users is still unknown. This study compared the music-remixing preferences of nine postlingually deaf, late-implanted CI users and seven prelingually deaf, early-implanted CI users, as well as their ratings of song familiarity and vocal pleasantness. Twelve songs were selected from the most streamed tracks on Spotify for testing. There were six remixed versions of each song: Original, Music-6 (6-dB attenuation of all instruments), Music-12 (12-dB attenuation of all instruments), Music-3-3-12 (3-dB attenuation of bass and drums and 12-dB attenuation of other instruments), Vocals-6 (6-dB attenuation of vocals), and Vocals-12 (12-dB attenuation of vocals). It was found that the prelingual group preferred the Music-6 and Original versions over the other versions, while the postlingual group preferred the Vocals-12 version over the Music-12 version. The prelingual group was more familiar with the songs than the postlingual group. However, the song familiarity rating did not significantly affect the patterns of preference ratings in each group. The prelingual group also had higher vocal pleasantness ratings than the postlingual group. For the prelingual group, higher vocal pleasantness led to higher preference ratings for the Music-12 version. For the postlingual group, their overall preference for the Vocals-12 version was driven by their preference ratings for songs with very unpleasant vocals. These results suggest that the patient factor of auditory experience and stimulus factor of vocal pleasantness may affect the music-remixing preferences of CI users. As such, the music-remixing strategy needs to be customized for individual patients and songs.
ContributorsVecellio, Amanda Paige (Author) / Luo, Xin (Thesis advisor) / Ringenbach, Shannon (Committee member) / Berisha, Visar (Committee member) / Zhou, Yi (Committee member) / Arizona State University (Publisher)
Created2024