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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- All Subjects: Speech
- Creators: Santello, Marco
- Creators: Turaga, Pavan
Description
This work examines two main areas in model-based time-varying signal processing with emphasis in speech processing applications. The first area concentrates on improving speech intelligibility and on increasing the proposed methodologies application for clinical practice in speech-language pathology. The second area concentrates on signal expansions matched to physical-based models but without requiring independent basis functions; the significance of this work is demonstrated with speech vowels.
A fully automated Vowel Space Area (VSA) computation method is proposed that can be applied to any type of speech. It is shown that the VSA provides an efficient and reliable measure and is correlated to speech intelligibility. A clinical tool that incorporates the automated VSA was proposed for evaluation and treatment to be used by speech language pathologists. Two exploratory studies are performed using two databases by analyzing mean formant trajectories in healthy speech for a wide range of speakers, dialects, and coarticulation contexts. It is shown that phonemes crowded in formant space can often have distinct trajectories, possibly due to accurate perception.
A theory for analyzing time-varying signals models with amplitude modulation and frequency modulation is developed. Examples are provided that demonstrate other possible signal model decompositions with independent basis functions and corresponding physical interpretations. The Hilbert transform (HT) and the use of the analytic form of a signal are motivated, and a proof is provided to show that a signal can still preserve desirable mathematical properties without the use of the HT. A visualization of the Hilbert spectrum is proposed to aid in the interpretation. A signal demodulation is proposed and used to develop a modified Empirical Mode Decomposition (EMD) algorithm.
A fully automated Vowel Space Area (VSA) computation method is proposed that can be applied to any type of speech. It is shown that the VSA provides an efficient and reliable measure and is correlated to speech intelligibility. A clinical tool that incorporates the automated VSA was proposed for evaluation and treatment to be used by speech language pathologists. Two exploratory studies are performed using two databases by analyzing mean formant trajectories in healthy speech for a wide range of speakers, dialects, and coarticulation contexts. It is shown that phonemes crowded in formant space can often have distinct trajectories, possibly due to accurate perception.
A theory for analyzing time-varying signals models with amplitude modulation and frequency modulation is developed. Examples are provided that demonstrate other possible signal model decompositions with independent basis functions and corresponding physical interpretations. The Hilbert transform (HT) and the use of the analytic form of a signal are motivated, and a proof is provided to show that a signal can still preserve desirable mathematical properties without the use of the HT. A visualization of the Hilbert spectrum is proposed to aid in the interpretation. A signal demodulation is proposed and used to develop a modified Empirical Mode Decomposition (EMD) algorithm.
ContributorsSandoval, Steven, 1984- (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Liss, Julie M (Committee member) / Turaga, Pavan (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2016
Description
Information processing in the brain is mediated by network interactions between anatomically distant (centimeters apart) regions of cortex and network action is fundamental to human behavior. Disruptive activity of these networks may allow a variety of diseases to develop. Degradation or loss of network function in the brain can affect many aspects of the human experience; motor disorder, language difficulties, memory loss, mood swings, and more. The cortico-basal ganglia loop is a system of networks in the brain between the cortex, basal ganglia, the thalamus, and back to the cortex. It is not one singular circuit, but rather a series of parallel circuits that are relevant towards motor output, motor planning, and motivation and reward. Studying the relationship between basal ganglia neurons and cortical local field potentials may lead to insights about neurodegenerative diseases and how these diseases change the cortico-basal ganglia circuit. Speech and language are uniquely human and require the coactivation of several brain regions. The various aspects of language are spread over the temporal lobe and parts of the occipital, parietal, and frontal lobe. However, the core network for speech production involves collaboration between phonologic retrieval (encoding ideas into syllabic representations) from Wernicke’s area, and phonemic encoding (translating syllables into motor articulations) from Broca’s area. Studying the coactivation of these brain regions during a repetitive speech production task may lead to a greater understanding of their electrophysiological functional connectivity. The primary purpose of the work presented in this document is to validate the use of subdural microelectrodes in electrophysiological functional connectivity research as these devices best match the spatial and temporal scales of brain activity. Neuron populations in the cortex are organized into functional units called cortical columns. These cortical columns operate on the sub-millisecond temporal and millimeter spatial scale. The study of brain networks, both in healthy and unwell individuals, may reveal new methodologies of treatment or management for disease and injury, as well as contribute to our scientific understanding of how the brain works.
ContributorsO'Neill, Kevin John (Author) / Greger, Bradley (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen (Committee member) / Papandreou-Suppapola, Antonia (Committee member) / Kleim, Jeffery (Committee member) / Arizona State University (Publisher)
Created2021