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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
The wide adoption and continued advancement of information and communications technologies (ICT) have made it easier than ever for individuals and groups to stay connected over long distances. These advances have greatly contributed in dramatically changing the dynamics of the modern day workplace to the point where it is now commonplace to see large, distributed multidisciplinary teams working together on a daily basis. However, in this environment, motivating, understanding, and valuing the diverse contributions of individual workers in collaborative enterprises becomes challenging. To address these issues, this thesis presents the goals, design, and implementation of Taskville, a distributed workplace game played by teams on large, public displays. Taskville uses a city building metaphor to represent the completion of individual and group tasks within an organization. Promising results from two usability studies and two longitudinal studies at a multidisciplinary school demonstrate that Taskville supports personal reflection and improves team awareness through an engaging workplace activity.
ContributorsNikkila, Shawn (Author) / Sundaram, Hari (Thesis advisor) / Byrne, Daragh (Committee member) / Davulcu, Hasan (Committee member) / Olson, Loren (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
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 is strongly desired. A latent topic models-based method is proposed to learn supra-segmental features from low-level acoustic descriptors. The derived features outperform state-of-the-art approaches over multiple databases. Cross-corpus studies are conducted to determine the ability of these features to generalize well across different databases. The proposed method is also applied to derive features from facial expressions; a multi-modal fusion overcomes the deficiencies of a speech only approach and further improves the recognition performance.
Besides affecting the acoustic properties of speech, emotions have a strong influence over speech articulation kinematics. A learning approach, which constrains a classifier trained over acoustic descriptors, to also model articulatory data is proposed here. This method requires articulatory information only during the training stage, thus overcoming the challenges inherent to large-scale data collection, while simultaneously exploiting the correlations between articulation kinematics and acoustic descriptors to improve the accuracy of emotion recognition systems.
Identifying context from ambient sounds in a lifelogging scenario requires feature extraction, segmentation and annotation techniques capable of efficiently handling long duration audio recordings; a complete framework for such applications is presented. The performance is evaluated on real world data and accompanied by a prototypical Android-based user interface.
The proposed methods are also assessed in terms of computation and implementation complexity. Software and field programmable gate array based implementations are considered for emotion recognition, while virtual platforms are used to model the complexities of lifelogging. The derived metrics are used to determine the feasibility of these methods for applications requiring real-time capabilities and low power consumption.
The expression and perception of emotions varies across speakers and cultures, thus, determining features and classification methods that generalize well to different conditions is strongly desired. A latent topic models-based method is proposed to learn supra-segmental features from low-level acoustic descriptors. The derived features outperform state-of-the-art approaches over multiple databases. Cross-corpus studies are conducted to determine the ability of these features to generalize well across different databases. The proposed method is also applied to derive features from facial expressions; a multi-modal fusion overcomes the deficiencies of a speech only approach and further improves the recognition performance.
Besides affecting the acoustic properties of speech, emotions have a strong influence over speech articulation kinematics. A learning approach, which constrains a classifier trained over acoustic descriptors, to also model articulatory data is proposed here. This method requires articulatory information only during the training stage, thus overcoming the challenges inherent to large-scale data collection, while simultaneously exploiting the correlations between articulation kinematics and acoustic descriptors to improve the accuracy of emotion recognition systems.
Identifying context from ambient sounds in a lifelogging scenario requires feature extraction, segmentation and annotation techniques capable of efficiently handling long duration audio recordings; a complete framework for such applications is presented. The performance is evaluated on real world data and accompanied by a prototypical Android-based user interface.
The proposed methods are also assessed in terms of computation and implementation complexity. Software and field programmable gate array based implementations are considered for emotion recognition, while virtual platforms are used to model the complexities of lifelogging. The derived metrics are used to determine the feasibility of these methods for applications requiring real-time capabilities and low power consumption.
ContributorsShah, Mohit (Author) / Spanias, Andreas (Thesis advisor) / Chakrabarti, Chaitali (Thesis advisor) / Berisha, Visar (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2015
Description
A myriad of social media services are emerging in recent years that allow people to communicate and express themselves conveniently and easily. The pervasive use of social media generates massive data at an unprecedented rate. It becomes increasingly difficult for online users to find relevant information or, in other words, exacerbates the information overload problem. Meanwhile, users in social media can be both passive content consumers and active content producers, causing the quality of user-generated content can vary dramatically from excellence to abuse or spam, which results in a problem of information credibility. Trust, providing evidence about with whom users can trust to share information and from whom users can accept information without additional verification, plays a crucial role in helping online users collect relevant and reliable information. It has been proven to be an effective way to mitigate information overload and credibility problems and has attracted increasing attention.
As the conceptual counterpart of trust, distrust could be as important as trust and its value has been widely recognized by social sciences in the physical world. However, little attention is paid on distrust in social media. Social media differs from the physical world - (1) its data is passively observed, large-scale, incomplete, noisy and embedded with rich heterogeneous sources; and (2) distrust is generally unavailable in social media. These unique properties of social media present novel challenges for computing distrust in social media: (1) passively observed social media data does not provide necessary information social scientists use to understand distrust, how can I understand distrust in social media? (2) distrust is usually invisible in social media, how can I make invisible distrust visible by leveraging unique properties of social media data? and (3) little is known about distrust and its role in social media applications, how can distrust help make difference in social media applications?
The chief objective of this dissertation is to figure out solutions to these challenges via innovative research and novel methods. In particular, computational tasks are designed to {\it understand distrust}, a innovative task, i.e., {\it predicting distrust} is proposed with novel frameworks to make invisible distrust visible, and principled approaches are develop to {\it apply distrust} in social media applications. Since distrust is a special type of negative links, I demonstrate the generalization of properties and algorithms of distrust to negative links, i.e., {\it generalizing findings of distrust}, which greatly expands the boundaries of research of distrust and largely broadens its applications in social media.
As the conceptual counterpart of trust, distrust could be as important as trust and its value has been widely recognized by social sciences in the physical world. However, little attention is paid on distrust in social media. Social media differs from the physical world - (1) its data is passively observed, large-scale, incomplete, noisy and embedded with rich heterogeneous sources; and (2) distrust is generally unavailable in social media. These unique properties of social media present novel challenges for computing distrust in social media: (1) passively observed social media data does not provide necessary information social scientists use to understand distrust, how can I understand distrust in social media? (2) distrust is usually invisible in social media, how can I make invisible distrust visible by leveraging unique properties of social media data? and (3) little is known about distrust and its role in social media applications, how can distrust help make difference in social media applications?
The chief objective of this dissertation is to figure out solutions to these challenges via innovative research and novel methods. In particular, computational tasks are designed to {\it understand distrust}, a innovative task, i.e., {\it predicting distrust} is proposed with novel frameworks to make invisible distrust visible, and principled approaches are develop to {\it apply distrust} in social media applications. Since distrust is a special type of negative links, I demonstrate the generalization of properties and algorithms of distrust to negative links, i.e., {\it generalizing findings of distrust}, which greatly expands the boundaries of research of distrust and largely broadens its applications in social media.
ContributorsTang, Jiliang (Author) / Liu, Huan (Thesis advisor) / Xue, Guoliang (Committee member) / Ye, Jieping (Committee member) / Aggarwal, Charu (Committee member) / Arizona State University (Publisher)
Created2015
Description
Study in user experience design states that there is a considerable gap between users and designers. Collaborative design and empathetic design methods attempt to make a strong relationship between these two. In participatory design activities, projective `make tools' are required for users to show their thoughts. This research is designed to apply an empathetic way of using `make tools' in user experience design for websites clients, users, and designers.
A magnetic wireframe tool has been used as a `make tool', and a sample project has been defined in order to see how the tool can create empathy among stakeholders. In this study fourth year graphic design students at Arizona State University (ASU), USA, are participating as users, faculty members have the role of clients, and Forty, Inc., a design firm in the Phoenix area, is the design team for the study. All of these three groups are cooperating on re-designing the homepage of the Design School in Herberger Institute for Design and Art (HIDA) at ASU.
A method for applying the magnetic tool was designed and used for each group. Results of users and clients' activities were shared with the design team, and they designed a final prototype for the wireframe of the sample project. Observation and interviews were done to see how participants work with the tool. Also, follow up questionnaires were used in order to evaluate all groups' experiences with the magnetic wireframe. Lastly, as a part of questionnaires, a sentence completion method has been used in order to collect the participants' exact thoughts about the magnetic tool.
Observations and results of data analysis in this research show that the tool was a helpful `make tool' for users and clients. They could talk about their ideas and also designers could learn more about people. The entire series of activities caused an empathetic relationship among stakeholders of the sample project. This method of using `make tools' in user experience design for web sites can be useful for collaborative UX design activities and further research in user experience design with empathy.
A magnetic wireframe tool has been used as a `make tool', and a sample project has been defined in order to see how the tool can create empathy among stakeholders. In this study fourth year graphic design students at Arizona State University (ASU), USA, are participating as users, faculty members have the role of clients, and Forty, Inc., a design firm in the Phoenix area, is the design team for the study. All of these three groups are cooperating on re-designing the homepage of the Design School in Herberger Institute for Design and Art (HIDA) at ASU.
A method for applying the magnetic tool was designed and used for each group. Results of users and clients' activities were shared with the design team, and they designed a final prototype for the wireframe of the sample project. Observation and interviews were done to see how participants work with the tool. Also, follow up questionnaires were used in order to evaluate all groups' experiences with the magnetic wireframe. Lastly, as a part of questionnaires, a sentence completion method has been used in order to collect the participants' exact thoughts about the magnetic tool.
Observations and results of data analysis in this research show that the tool was a helpful `make tool' for users and clients. They could talk about their ideas and also designers could learn more about people. The entire series of activities caused an empathetic relationship among stakeholders of the sample project. This method of using `make tools' in user experience design for web sites can be useful for collaborative UX design activities and further research in user experience design with empathy.
ContributorsEslamifar, Ali (Author) / Heywood, William (Thesis advisor) / Walker, Erin (Committee member) / Takamura, John (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
Although there are many forms of organization on the Web, one of the most prominent ways to organize web content and websites are tags. Tags are keywords or terms that are assigned to a specific piece of content in order to help users understand the common relationships between pieces of content. Tags can either be assigned by an algorithm, the author, or the community. These tags can also be organized into tag clouds, which are visual representations of the structure and organization contained implicitly within these tags. Importantly, little is known on how we use these different tagging structures to understand the content and structure of a given site. This project examines 2 different characteristics of tagging structures: font size and spatial orientation. In order to examine how these different characteristics might interact with individual differences in attentional control, a measure of working memory capacity (WMC) was included. The results showed that spatial relationships affect how well users understand the structure of a website. WMC was not shown to have any significant effect; neither was varying the font size. These results should better inform how tags and tag clouds are used on the Web, and also provide an estimation of what properties to include when designing and implementing a tag cloud on a website.
ContributorsBanas, Steven (Author) / Sanchez, Christopher A (Thesis advisor) / Branaghan, Russell (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2011