Bachelor of Science of Media Arts and Studies (BSC), Ohio University, 2010, Media Arts and Studies

Forensic audio analysis and audio restoration are two formerly obscure fields that are becoming increasingly important to society. Despite being daunting in name, both fields are actually just specialized forms of audio production – the same type of audio production taught in Ohio University's School of Media Arts and Studies. This thesis aims to illustrate how connected audio restoration and forensic audio analysis are and how those two fields relate to traditionally taught audio production. Furthermore this thesis will provide some of the social and pedagogical advantages to teaching forensic audio analysis and restoration at the undergraduate level as a component of a complete audio sequence, as well as offer an example of a complete course curriculum that can be used for such education.

Committee: Eddie Ashworth (Advisor) Subjects: Communication; Criminology; Education; Mass Media

Master of Science in Engineering, University of Akron, 2018, Electrical Engineering

Beamforming is a signal processing technique that is utilized in many communications and signal processing applications. Beamformers help to improve signal quality and enhance the performance of sensor networks and communications arrays. Current digital design methods may require the use of an FPGA or ASIC to perform signal processing. These implementations can be very expensive in terms of design cost and production cost. For this reason, it is worth investigating analog design approaches which can be implemented efficiently and inexpensively using analog design techniques. This thesis explores the recent developments in method and algorithm, and demonstrates applicability to analog beamforming. Two algorithms are investigated and tested: the Delay Vandermonde Matrix (DVM) and a novel analog implementation of the Farrow filter. The DVM design implements a five-beam multi-beam beamformer while the analog Farrow filter implements a single beam which is steerable in the range of 0º to 60º. These two algorithms are analyzed in the analog domain and prototype designs were developed, built, and tested in the laboratory. The prototype designs implemented audio beam-forming using analog electronic components for a four-element array of miniature speaker drivers. A 64-element array of miniature speaker drivers was also analyzed and tested using the same prototype designs. The results from these prototype designs were analyzed and show that a 10dB to 15dB beam intensity can be achieved with the speaker arrays. The results demonstrate that the analog design approach can be a viable and cost effective alternative to typical digital design approaches. This research may have specific applications to teleconference, home theater, virtual reality, and other audio applications.

Committee: Arjuna Madanayake PhD (Advisor); Hamid Bahrami PhD (Committee Member); Kye-Shin Lee PhD (Committee Member) Subjects: Acoustics; Computer Engineering; Electrical Engineering; Engineering

Master of Science (MS), Wright State University, 2007, Human Factors and Industrial/Organizational Psychology MS

Previous research on aurally-aided visual search has repeatedly shown a significant reduction in response times when displaying 3D auditory cues. However, the vast majority of this research has only examined searches for static (non-moving) targets in static visual environments. In the present study, visual search performance in both static and dynamic (moving) visual environments is examined with and without virtual 3D auditory cues. In both static and dynamic environments, and for all observers, visual search times were significantly reduced when auditory spatial cues were displayed. Auditory cues provided the largest benefits when the target initially appeared at farther eccentricities and on the horizontal axis. General practice effects were observed, but 3D auditory cues were immediately effective with little or no time needed for learning. Overall, the results suggest a similar and consistent performance benefit offered by 3D audio for both static and dynamic environments.

Committee: Scott Watamaniuk (Advisor) Subjects: Psychology, Experimental

Master of Science in Computer Engineering (MSCE), Wright State University, 2025, Computer Engineering

The rapid assessment of cardiac arrhythmias remains critical in emergency healthcare settings, where traditional ECG interpretation methods often require specialized expertise and considerable time. The integration of acoustic transformation with electrocardiogram analysis presents a groundbreaking methodology for quantifying arrhythmia severity in clinical settings. By converting electrical cardiac signals into auditory waveforms, this approach unlocks distinctive spectral and temporal characteristics that remain imperceptible in visual ECG interpretation. This sonification process creates a rich multi-dimensional dataset where subtle variations in rhythm, amplitude, and frequency directly correlate with physiological abnormalities. The acoustic domain provides unique insights into the chaotic patterns characteristic of severe arrhythmias, particularly in cases of atrial and ventricular fibrillation where traditional ECG interpretation frequently encounters ambiguity in severity classification. The developed computational framework leverages multi-domain feature extraction techniques to build comprehensive arrhythmia profiles from sonified ECG data. The system automatically identifies and processes peak distance metrics, wavelet coefficients, spectral entropy variations, and temporal rhythm irregularities to construct a severity scoring mechanism. This hybrid approach draws strength from both time-domain analysis, capturing instantaneous rhythm disruptions, and frequency-domain examination, revealing harmonic distortions characteristic of severe cardiac dysfunction. By simultaneously analyzing these complementary feature sets, the system overcomes the limitations of single-domain approaches, achieving remarkable discrimination between mild, moderate, severe, and critical arrhythmic conditions even in complex cases where conventional algorithms typically falter. Experimental results comprehensively validate that this ECG-to-audio sonification system outperfor (open full item for complete abstract)

Committee: Fathi Amsaad, Ph.D. (Advisor); Darryl Ahner, Ph.D. (Advisor); Bin Wang, Ph.D. (Committee Member); Ahsan Mian, Ph.D. (Committee Member); Thomas Wischgoll, Ph.D. (Other); Subhashini Ganapathy, Ph.D. (Other) Subjects: Biomedical Research; Computer Engineering; Computer Science; Electrical Engineering; Health Sciences

Bachelor of Science (BS), Ohio University, 2025, Media Arts and Studies

For my creative project, I created a digital synthesizer with audio-reactive visuals in the program Max. I learned the core components of a digital synthesizer and how they worked as well as the methods of creating reactive visuals. I implemented what I had learned to create a bespoke instrument made for improvisational performance. The goal was to create a synthesizer that had enough control outside of the mouse and keyboard such that it felt as comfortable as a non-digital instrument. In addition to synthesizing music, I also wanted to synthesize visuals that would be reactive to the music.

Committee: Robert McClure Dr. (Advisor) Subjects: Multimedia Communications; Music; Performing Arts

Master of Science in Electrical Engineering (MSEE), Wright State University, 2017, Electrical Engineering

Many companies in the music industry offer programmable preset guitar pedals. Presets allow musicians to save time and focus on their act by recalling predetermined settings during a performance. A majority of the companies in the music industry offer up to hundreds of presets, but realistically the substantial amount of presets may have a negative effect on the musician's performance due to time constraints. The main contribution of this thesis is to address the musician by reducing the amount of presets offered in a guitar pedal design. Combining two systems, a digital control and audio processing circuit, will produce a programmable four-preset guitar pedal. Cost and size are design constraints that will also be taken into consideration. The techniques observed in this thesis will benefit the music industry because they can be adapted into other guitar pedal designs. This thesis closes with an evaluation of the final design, feedback from musicians in the community, and suggestions for future improvements.

Committee: Marian Kazimierczuk Ph.D. (Advisor); Joe Tritschler Ph.D. (Committee Member); Yan Zhuang Ph.D. (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 1965, Graduate School

Committee: Not Provided (Other) Subjects: Education

Doctor of Philosophy, The Ohio State University, 1961, Graduate School

Committee: Not Provided (Other) Subjects: Education

BA, Oberlin College, 2016, Computer Science

This paper presents elaborations upon the beam tracing algorithm first introduced to acoustic research in 1998. Beam tracing for audio approximates reverberation filters present in physical architectural scenes by analyzing digital models of those scenes to compose the impulse responses of those filters. The algorithm as originally presented takes into account some of the acoustic absorption properties of the materials making up the scene. However, it has previously assumed that each surface which reflects or transmits sound does so at an even distribution across the space of audible frequencies. This paper describes a method for incorporating non-flat frequency responses of surfaces, which resolves this shortcoming. A survey of human subjects confirms that after these improvements, the algorithm produces more convincing and realistic filters.

Committee: Robert Geitz (Advisor) Subjects: Acoustics; Architecture; Computer Engineering; Computer Science; Music

Bachelor of Science of Media Arts and Studies (BSC), Ohio University, 2012, Media Arts and Studies

Examination of the history, development, and future of adaptive, dynamic, and interactive music in video games. Discussions include nonlinear music historical developments, compositional approaches for adaptive music, generative music, testing methods in the compositional and implementation stages, the evolving industry of adaptive music composition, future technological developments in music production and gaming, and adaptive music beyond games. Also included is an appendix of video game case studies, as well as an appendix of professional insight from game industry veterans.

Committee: Eddie Ashworth (Advisor); Arthur Cromwell Dr. (Other) Subjects: Communication; Composition; Mass Media; Music; Technology

MS, Kent State University, 2007, College of Arts and Sciences / Department of Computer Science

Audio perception is highly susceptible to disturbance in temporal quality. In the event of congestion, audio datagrams suffer packet loss, delay and jitter. Compressed audio appears as one of the most delicate traffic-type to handle on the Internet. The recent advances in auditory perception promise opportunities where a perceptually clever adaptive audio system can respond to impending breakdown and support near flawless sound. However, the major problem is receiving fast feedback from the current Internet. Recently proposed TCP Interactive (iTCP) seems to offer some interesting opportunity to perceptual audio. This is an operational state equivalent to the conventional TCP except that applications can optionally subscribe and receive selected local end-point protocol events in real-time. In this thesis, we implemented a novel symbiotic perceptual audio streaming mechanism, that receives fast feedback from iTCP about congestion and then responds appropriately. This mechanism combines the quantization technique to accurately represent the audio signals without distortion. The adaptive system reduces the encoding target bit rate when congestion is detected which invariably reduces the delay and jitter faced by audio traffic in the network during congestion. We have tested it over the Internet. In this thesis, we highlight the performance of this system and report on the dramatic improvements in time-bounded streaming audio we observed.

Committee: Javed Khan (Advisor) Subjects:

MFA, Kent State University, 2026, College of Communication and Information / School of Visual Communication Design

Innovation in museum exhibition design can have positive side effects that reduce factors contributing to museum fatigue by providing a variety of styles for visitors to take in information. This thesis explores the use of information delivered in an audio format, without the addition of the written word. Participants tested needed some guidance on how to interact with the created exhibit, but once understanding the system, all participants connected with the material and learned or heard something new. With the success of the audio information delivery, museum professionals can confidently move away from the standard of written label text to convey information and can take more risks to entice and engage visitors.

Committee: Jessica Barness (Advisor); Jeff Polunas (Committee Member); David Wilson (Committee Member) Subjects: Design; Museum Studies

Master of Computer Science (M.C.S.), University of Dayton, 2026, Computer Science

Intelligent networks are rapidly advancing in their capabilities of producing seemingly authentic media, especially in areas related to text and image generation. In this paper, we propose an artificial intelligence-based model structure designed to produce authentic-sounding classical piano music. We combine the capabilities of WaveNet, a neural network created to autoregressively generate audio, and the variational autoencoder, a structure of model that learns to represent data in a continuous latent distribution. The model is trained on a dataset of classical piano music and then used to generate new synthetic music samples. During the generative process, we provide the model with different contexts that aid in informing its outputs. Our experimental results demonstrate that a WaveNet-based variational autoencoder is effective at modeling the data for digitized piano audio, but these results come up well short of passing as genuine piano audio. We conclude that this model structure has the potential to produce compelling audio data, but such results will likely require an extensive amount of training time to achieve.

Committee: Ju Shen (Advisor); Tianming Zhao (Committee Member); Zhongmei Yao (Committee Member); Tam Nguyen (Committee Chair) Subjects: Artificial Intelligence; Computer Science

PhD, University of Cincinnati, 2025, Arts and Sciences: English

This dissertation delineates a counter-representational conception of poetics by privileging medial and modal dimensions of poetry. A non-representational conception of poetics based on presence or absence of a coherent speaker is inadequate for differentiating the “experimental” and “mainstream” tendencies in contemporary U.S. poetry. Instead, this dissertation proposes computational and materialist approaches that revolve around these fundamental questions: How might we delimit the domain of poetics in the digital age? What will its aims and objectives look like? Its techniques and methods? Digitization of poetry and poetry-related contents has widened the domain of postwar U.S. poetry by making available hitherto inaccessible print- and audio-texts, and we are poised to use data science and digital humanities methods to analyze the internal differences among the variety of poetic formations in the period. Leveraging the audio archives of poetry recordings in the postwar period as the primary object of study, I developed multiple linked data infrastructures and literary industry analytics and visualization platforms that take into account literary circulation as a whole. I draw upon techniques from computational social science (social network analysis), data science (natural language processing), and linguistics (intonational phonology) to model the materials and forces that condition the distribution, reception, and production of postwar U.S. poetry, respectively. The goal of this research is to situate the poetry reading series and the Program Era (alongside the postmodern avant-garde, of course) as two emergent phenomena of the postwar period. Unlike the current proposal in digital humanities to combine close and distant readings, this dissertation proposes a diagrammatic approach to repurposing scientific techniques for modeling humanities data and delineating a research program in digital poetics.

Committee: Julia Carlson Ph.D. (Committee Chair); James Lee Ph.D. (Committee Member); Aditi Machado Ph.D. (Committee Member); Lisa Hogeland Ph.D. (Committee Member) Subjects: American Literature

Master of Science, The Ohio State University, 1978, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1975, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Arts, The Ohio State University, 1981, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1979, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1979, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Arts, The Ohio State University, 1984, Graduate School

Committee: Not Provided (Other) Subjects: