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Description
This project sheds light on trombonist Andy Martin's improvisation and provides tools for further learning. A biographical sketch gives background on Martin, establishing him as a newer jazz master. Through the transcription and analysis of nine improvised solos, Martin's improvisational voice and vocabulary is deciphered and presented as a series of seven thematic hooks. These patterns, rhythms, and gestures are described, analyzed, and presented as examples of how each is used in the solos. The hooks are also set as application exercises for learning jazz style and improvisation. These exercises demonstrate how to use Martin's hooks as a means for furthering one's own improvisation. A full method for successful transcription is also presented, along with the printed transcriptions and their accompanying information sheets.
ContributorsWilkinson, Michael Scott (Author) / Ericson, John (Thesis advisor) / Kocour, Michael (Committee member) / Solis, Theodore (Committee member) / Arizona State University (Publisher)
Created2013
Description
Jazz continues, into its second century, as one of the most important musics taught in public middle and high schools. Even so, research related to how students learn, especially in their earliest interactions with jazz culture, is limited. Weaving together interviews and observations of junior and senior high school jazz players and teachers, private studio instructors, current university students majoring in jazz, and university and college jazz faculty, I developed a composite sketch of a secondary school student learning to play jazz. Using arts-based educational research methods, including the use of narrative inquiry and literary non-fiction, the status of current jazz education and the experiences by novice jazz learners is explored. What emerges is a complex story of students and teachers negotiating the landscape of jazz in and out of early twenty-first century public schools. Suggestions for enhancing jazz experiences for all stakeholders follow, focusing on access and the preparation of future jazz teachers.
ContributorsKelly, Keith B (Author) / Stauffer, Sandra (Thesis advisor) / Tobias, Evan (Committee member) / Kocour, Michael (Committee member) / Sullivan, Jill (Committee member) / Schmidt, Margaret (Committee member) / Arizona State University (Publisher)
Created2013
Description
Concerto for Piano and Chamber Orchestra was conceived in February of 2013, and conceptually it is my attempt to fuse personal expressions of jazz and classical music into one fully realized statement. It is a three movement work (fast, slow, fast) for 2 fl., 2 ob., 2 cl., bsn., 2 hrn., 2 tpt., tbn., pno., perc., str. (6,4,2,2,1). The work is approximately 27 minutes in duration. The first movement of the Concerto is written in a fluid sonata form. A fugato begins where the second theme would normally appear, and the second theme does not fully appear until near the end of the solo piano section. The result is that the second theme when finally revealed is so reminiscent of the history of jazz and classical synthesis that it does not sound completely new, and in fact is a return of something that was heard before, but only hinted at in this piece. The second movement is a kind of deconstructive set of variations, with a specific theme and harmonic pattern implied throughout the movement. However, the full theme is not disclosed until the final variation. The variations are interrupted by moments of pure rhythmic music, containing harmony made up of major chords with an added fourth, defying resolution, and dissolving each time back into a new variation. The third movement is in rondo form, using rhythmic and harmonic influences from jazz. The percussion plays a substantial role in this movement, acting as a counterpoint to the piano part throughout. This movement and the piece concludes with an extended coda, inspired indirectly by the simple complexities of an improvisational piano solo, building in complexity as the concerto draws to a close.
ContributorsSneider, Elliot (Author) / Rogers, Rodney (Thesis advisor) / DeMars, James (Committee member) / Hackbarth, Glenn (Committee member) / Solis, Theodore (Committee member) / Arizona State University (Publisher)
Created2013
Description
Many learning models have been proposed for various tasks in visual computing. Popular examples include hidden Markov models and support vector machines. Recently, sparse-representation-based learning methods have attracted a lot of attention in the computer vision field, largely because of their impressive performance in many applications. In the literature, many of such sparse learning methods focus on designing or application of some learning techniques for certain feature space without much explicit consideration on possible interaction between the underlying semantics of the visual data and the employed learning technique. Rich semantic information in most visual data, if properly incorporated into algorithm design, should help achieving improved performance while delivering intuitive interpretation of the algorithmic outcomes. My study addresses the problem of how to explicitly consider the semantic information of the visual data in the sparse learning algorithms. In this work, we identify four problems which are of great importance and broad interest to the community. Specifically, a novel approach is proposed to incorporate label information to learn a dictionary which is not only reconstructive but also discriminative; considering the formation process of face images, a novel image decomposition approach for an ensemble of correlated images is proposed, where a subspace is built from the decomposition and applied to face recognition; based on the observation that, the foreground (or salient) objects are sparse in input domain and the background is sparse in frequency domain, a novel and efficient spatio-temporal saliency detection algorithm is proposed to identify the salient regions in video; and a novel hidden Markov model learning approach is proposed by utilizing a sparse set of pairwise comparisons among the data, which is easier to obtain and more meaningful, consistent than tradition labels, in many scenarios, e.g., evaluating motion skills in surgical simulations. In those four problems, different types of semantic information are modeled and incorporated in designing sparse learning algorithms for the corresponding visual computing tasks. Several real world applications are selected to demonstrate the effectiveness of the proposed methods, including, face recognition, spatio-temporal saliency detection, abnormality detection, spatio-temporal interest point detection, motion analysis and emotion recognition. In those applications, data of different modalities are involved, ranging from audio signal, image to video. Experiments on large scale real world data with comparisons to state-of-art methods confirm the proposed approaches deliver salient advantages, showing adding those semantic information dramatically improve the performances of the general sparse learning methods.
ContributorsZhang, Qiang (Author) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (Committee member) / Wang, Yalin (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2014
Description
This multiple-case study addresses the nature of the out-of-school musical engagements of four undergraduate students who were enrolled as jazz studies majors in a large school of music in the U.S. southwest. It concerns what they did musically when they were outside of school, why they did what they did, what experiences they said they learned from, and how their out-of-school engagements related to their in-school curriculum. Research on jazz education, informal learning practices in music, and the in-school and out-of-school experiences of students informed this study. Data were generated through observation, interviews, video blogs (vlogs), and SMS text messages.
Analysis of data revealed that participants engaged with music when outside of school by practicing, teaching, gigging, recording, playing music with others, attending live musical performances, socializing with other musicians, listening, and engaging with non-jazz musical styles (aside from listening). They engaged with music because of: 1) the love of music, 2) the desire for musical excellence, 3) financial considerations, 4) the aspiration to affect others positively with music, and 5) the connection with other musicians. Participants indicated that they learned by practicing, listening to recordings, attending live performances, playing paid engagements, socializing, teaching, and reading. In-school and out-of-school experience and learning had substantial but not complete overlap.
The study implies that a balance between in-school and out-of-school musical experience may help undergraduate jazz studies students to maximize their overall musical learning. It also suggests that at least some jazz studies majors are fluent in a wide variety of music learning practices that make them versatile, flexible, and employable musicians. Further implications are provided for undergraduate jazz students as well as collegiate jazz educators, the music education profession, and schools of music. Additional implications concern future research and the characterization of jazz study in academia.
Analysis of data revealed that participants engaged with music when outside of school by practicing, teaching, gigging, recording, playing music with others, attending live musical performances, socializing with other musicians, listening, and engaging with non-jazz musical styles (aside from listening). They engaged with music because of: 1) the love of music, 2) the desire for musical excellence, 3) financial considerations, 4) the aspiration to affect others positively with music, and 5) the connection with other musicians. Participants indicated that they learned by practicing, listening to recordings, attending live performances, playing paid engagements, socializing, teaching, and reading. In-school and out-of-school experience and learning had substantial but not complete overlap.
The study implies that a balance between in-school and out-of-school musical experience may help undergraduate jazz studies students to maximize their overall musical learning. It also suggests that at least some jazz studies majors are fluent in a wide variety of music learning practices that make them versatile, flexible, and employable musicians. Further implications are provided for undergraduate jazz students as well as collegiate jazz educators, the music education profession, and schools of music. Additional implications concern future research and the characterization of jazz study in academia.
ContributorsLibman, Jeffrey B (Author) / Tobias, Evan (Thesis advisor) / Kocour, Michael (Committee member) / Schmidt, Margaret (Committee member) / Solis, Theodore (Committee member) / Stauffer, Sandra (Committee member) / Arizona State University (Publisher)
Created2014
Description
The study of artist transcriptions is an effective vehicle for assimilating the language and style of jazz. Pairing transcriptions with historical context provides further insight into the back story of the artists' life and method. Innovators are often the subject of published studies of this kind, but transcriptions of plunger-mute master Al Grey have been overlooked. This document fills that void, combining historical context with thirteen transcriptions of Grey's trombone features and improvisations. Selection of transcribed materials was based on an examination of historically significant solos in Al Grey's fifty-five-year career. The results are a series of open-horn and plunger solos that showcase Grey's sound, technical brilliance, and wide range of dynamics and articulation. This collection includes performances from a mix of widely available and obscure recordings, the majority coming from engagements with the Count Basie Orchestra. Methods learned from the study of Al Grey's book Plunger Techniques were vital in the realization of his work. The digital transcription software Amazing Slow Downer by Roni Music aided in deciphering some of Grey's more complicated passages and, with octave displacement, helped bring previously inaudible moments to the foreground.
ContributorsHopkins, Charles E (Author) / Pilafian, Sam (Thesis advisor) / Stauffer, Sandra (Committee member) / Solís, Ted (Committee member) / Ericson, John (Committee member) / Kocour, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study examines the experiences of participants enrolled in an online community college jazz history course. I surveyed the participants before the course began and observed them in the online space through the duration of the course. Six students also participated in interviews during and after the course. Coded data from the interviews, surveys, and recorded discussion posts and journal entries provided evidence about the nature of interaction and engagement in learning in an online environment. I looked for evidence either supporting or detracting from a democratic online learning environment, concentrating on the categories of student engagement, freedom of expression, and accessibility. The data suggested that the participants' behaviors in and abilities to navigate the online class were influenced by their pre-existing native media habits. Participants' reasons for enrolling in the online course, which included convenience and schedule flexibility, informed their actions and behaviors in the class. Analysis revealed that perceived positive student engagement did not contribute to a democratic learning environment but rather to an easy, convenient experience in the online class. Finally, the data indicated that participants' behaviors in their future lives would not be affected by the online class in that their learning experiences were not potent enough to alter or inform their behavior in society. As online classes gain popularity, the ability of these classes to provide meaningful learning experiences must be questioned. Students in this online jazz history class presented, at times, a façade of participation and community building but demonstrated a lack of sincerity and interest in the course. The learning environment supported accessibility and freedom of expression to an extent, but students' engagement with their peers was limited. Overall, this study found a need for more research into the quality of online classes as learning platforms that support democracy, student-to-student interaction, and community building.
ContributorsHunter, Robert W. (Author) / Stauffer, Sandra L (Thesis advisor) / Tobias, Evan (Thesis advisor) / Bush, Jeffrey (Committee member) / Kocour, Michael (Committee member) / Pilafian, Sam (Committee member) / Arizona State University (Publisher)
Created2011
Description
Sparse learning is a technique in machine learning for feature selection and dimensionality reduction, to find a sparse set of the most relevant features. In any machine learning problem, there is a considerable amount of irrelevant information, and separating relevant information from the irrelevant information has been a topic of focus. In supervised learning like regression, the data consists of many features and only a subset of the features may be responsible for the result. Also, the features might require special structural requirements, which introduces additional complexity for feature selection. The sparse learning package, provides a set of algorithms for learning a sparse set of the most relevant features for both regression and classification problems. Structural dependencies among features which introduce additional requirements are also provided as part of the package. The features may be grouped together, and there may exist hierarchies and over- lapping groups among these, and there may be requirements for selecting the most relevant groups among them. In spite of getting sparse solutions, the solutions are not guaranteed to be robust. For the selection to be robust, there are certain techniques which provide theoretical justification of why certain features are selected. The stability selection, is a method for feature selection which allows the use of existing sparse learning methods to select the stable set of features for a given training sample. This is done by assigning probabilities for the features: by sub-sampling the training data and using a specific sparse learning technique to learn the relevant features, and repeating this a large number of times, and counting the probability as the number of times a feature is selected. Cross-validation which is used to determine the best parameter value over a range of values, further allows to select the best parameter value. This is done by selecting the parameter value which gives the maximum accuracy score. With such a combination of algorithms, with good convergence guarantees, stable feature selection properties and the inclusion of various structural dependencies among features, the sparse learning package will be a powerful tool for machine learning research. Modular structure, C implementation, ATLAS integration for fast linear algebraic subroutines, make it one of the best tool for a large sparse setting. The varied collection of algorithms, support for group sparsity, batch algorithms, are a few of the notable functionality of the SLEP package, and these features can be used in a variety of fields to infer relevant elements. The Alzheimer Disease(AD) is a neurodegenerative disease, which gradually leads to dementia. The SLEP package is used for feature selection for getting the most relevant biomarkers from the available AD dataset, and the results show that, indeed, only a subset of the features are required to gain valuable insights.
ContributorsThulasiram, Ramesh (Author) / Ye, Jieping (Thesis advisor) / Xue, Guoliang (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
The solo repertoire from the Light Music Era serves as an important link between the Classical and Jazz soloist traditions. These characteristics are best highlighted through an analysis of three solo transcriptions: Felix Arndt's Nola as performed by Al Gallodoro, Rudy Wiedoeft's Valse Vanité, as performed by Freddy Gardener, and Jimmy Dorsey's Oodles of Noodles, as performed by Al Gallodoro. The transcriptions, done by the author, are taken from primary source recordings, and the ensuing analysis serves to show the saxophone soloists of the Light Music Era as an amalgamation of classical and jazz saxophone. Many of the works performed during the Light Music Era are extant only in recorded form. Even so, these performances possess great historical significance within the context of the state of the saxophone as an important solo instrument in the wider musical landscape. The saxophone solos from the Light Music Era distinguish themselves through the use of formal development and embellishment of standard "song forms" (such as ABA, and AABA), and the use of improvisational techniques that are common to early Jazz; however, the analysis shows that the improvisational techniques were distinctly different than a Jazz solo improvisation in nature. Although it has many characteristics in common with both "Classical Music" (this is used as a generic term to refer to the music of the Western European common practice period that is not Pop music or Jazz) and Jazz, the original research shows that the saxophone solo music from the Light Music Era is a distinctly original genre due to the amalgamation of seemingly disparate elements.
ContributorsPuccio, Dan (Author) / Mcallister, Timothy P (Thesis advisor) / Feisst, Sabine (Committee member) / Kocour, Michael (Committee member) / Pilafian, J. Samuel (Committee member) / Spring, Robert (Committee member) / Arizona State University (Publisher)
Created2012
Description
New music is often created as a product of commissions resulting in a collaborative effort between the performer and the composer. This performer-composer relationship represents an important component of the role of the artist in expanding the repertoire of the instrument. Belgian composer, Norbert Goddaer (b. 1933), has written numerous works for clarinet that are the result of such collaborations. Mr. Goddaer's works for clarinet are well-crafted and audience-friendly, and are thus good programming choices for students and professionals alike. His clarinet works have been performed worldwide in artist recitals, conferences for organizations such as the International Clarinet Association, The Midwest Clinic, and the Texas Music Educators Association, and have been commercially recorded and released by some of the foremost contemporary clarinet artists. These works have a great education value given the fact that they are appropriate choices for such a wide range of clarinetists. In an effort to contribute to this body of performance history, the author has produced a recording of five of Goddaer's previously unrecorded works, accompanied by a performance guide to each work. This document provides detailed performance notes with corresponding musical examples, basic formal analyses, and musical suggestions for Las Mañas, Conversations, Ballad, Duets, and Restless by Norbert Goddaer. The author has included a full transcript of an interview with Norbert Goddaer, which includes a first-person discussion of each work, and additionally includes biographical information supported by concert programs and an annotated list of all of Goddaer's works for clarinet, and a discography of his works for clarinet.
ContributorsClasen, Kevin (Author) / Spring, Robert S (Thesis advisor) / Gardner, Joshua T (Committee member) / Norton, Kay (Committee member) / Hill, Gary (Committee member) / McAllister, Timothy (Committee member) / Arizona State University (Publisher)
Created2012