"It makes you think anything is possible”: Representing diversity in music theory pedagogy

This paper critiques a traditional approach to music theory pedagogy. It argues that music theory courses should draw on pedagogies that reflect the diversity and pluralism inherent in 21st century music making. It presents the findings of an action research project investigating the experiences of undergraduate students undertaking an innovative contemporary art music theory course. It describes the students’ struggle in coming to terms with a course that integrated composing, performing, listening and analysing coupled with what for many was their first exposure to the diversity of contemporary art music. The paper concludes with suggesting that the approach could be adopted more widely throughout music programs.

Changing musical emotion : a computational rule system for modifying score and performance

When communicating emotion in music, composers and performers encode their expressive intentions through the control of basic musical features such as: pitch, loudness, timbre, mode, and articulation. The extent to which emotion can be controlled through the systematic manipulation of these features has not been fully examined. In this paper we present CMERS, a Computational Music Emotion Rule System for the control of perceived musical emotion that modifies features at the levels of score and performance in real-time. CMERS performance was evaluated in two rounds of perceptual testing. In experiment I, 20 participants continuously rated the perceived emotion of 15 music samples generated by CMERS. Three music works, each with five emotional variations were used (normal, happy, sad, angry, and tender). The intended emotion by CMERS was correctly identified 78% of the time, with significant shifts in valence and arousal also recorded, regardless of the works’ original emotion.

SoundCipher

The SoundCipher software library provides an easy way to create music in the Processing development environment. With the SoundCipher library added to Processing you can write software programs that make music to go along with your graphics and you can add sounds to enhance your Processing animations or games. SoundCipher provides an easy interface for playing 'notes' on the JavaSound synthesizer, for playback of audio files, and comunicating via MIDI. It provides accurate scheduling and allows events to be organised in musical time; using beats and tempo. It uses a 'score' metaphor that allows the construction of simple or complex musical arrangements. SoundCipher is designed to facilitate the basics of algorithmic music and interactive sound design as well as providing a platform for sophisticated computational music, it allows integration with the Minim library when more sophisticated audio and synthesis functionality is required and integration with the oscP5 library for communicating via open sound control.

Generation in context : an exploratory method for musical enquiry

This paper discusses a method, Generation in Context, for interrogating theories of music analysis and music perception. Given an analytic theory, the method consists of creating a generative process that implements the theory in reverse. Instead of using the theory to create analyses from scores, the theory is used to generate scores from analyses. Subjective evaluation of the quality of the musical output provides a mechanism for testing the theory in a contextually robust fashion. The method is exploratory, meaning that in addition to testing extant theories it provides a general mechanism for generating new theoretical insights. We outline our initial explorations in the use of generative processes for music research, and we discuss how generative processes provide evidence as to the veracity of theories about how music is experienced, with insights into how these theories may be improved and, concurrently, provide new techniques for music creation. We conclude that Generation in Context will help reveal new perspectives on our understanding of music.

Mind change complexity of learning logic programs

The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. This paper shows that an effective version of Shinohara’s notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. Let Omega be a notation for the first limit ordinal. Then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m >0, the class of languages defined by formal systems of length <= m: • is identifiable in the limit from positive data with a mind change bound of Omega (power)m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of Omega × m. The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded Prolog programs, including Shapiro’s linear programs, Arimura and Shinohara’s depth-bounded linearly covering programs, and Krishna Rao’s depth-bounded linearly moded programs. It is also noted that the bound for learning from positive data is tight for the example classes considered.

The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.

High Culture as Subculture : Brisbane's Contemporary Chamber Music Scene

The aim of the dissertation is to discover the extent to which methodologies and conceptual frameworks used to understand popular culture may also be useful in the attempt to understand contemporary high culture. The dissertation addresses this question through the application of subculture theory to Brisbane’s contemporary chamber music scene, drawing on a detailed case study of the contemporary chamber ensemble Topology and its audiences. The dissertation begins by establishing the logic and necessity of applying cultural studies methodologies to contemporary high culture. This argument is supported by a discussion of the conceptual relationships between cultural studies, high culture, and popular culture, and the methodological consequences of these relationships. In Chapter 2, a brief overview of interdisciplinary approaches to music reveals the central importance of subculture theory, and a detailed survey of the history of cultural studies research into music subcultures follows. Five investigative themes are identified as being crucial to all forms of contemporary subculture theory: the symbolic; the spatial; the social; the temporal; the ideological and political. Chapters 3 and 4 present the findings of the case study as they relate to these five investigative themes of contemporary subculture theory. Chapter 5 synthesises the findings of the previous two chapters, and argues that while participation in contemporary chamber music is not as intense or pervasive as is the case with the most researched street-based youth subcultures, it is nevertheless possible to describe Brisbane’s contemporary chamber music scene as a subculture. The dissertation closes by reflecting on the ways in which the subcultural analysis of contemporary chamber music has yielded some insight into the lived practices of high culture in contemporary urban contexts.

Soundcipher : a music and sound library for processing

SoundCipher is a software library written in the Java language that adds important music and sound features to the Processing environment that is widely used by media artists and otherwise has an orientation toward computational graphics. This article introduces the SoundCipher library and its features, describes its influences and design intentions, and positions it within the field of computer music programming tools. SoundCipher enables the rich history of algorithmic music techniques to be accessible within one of today’s most popular media art platforms. It also provides an accessible means for learning to create algorithmic music and sound programs.

TraSe algorithm : automatic evolutionary morphing of electronic dance music

The TraSe (Transform-Select) algorithm has been developed to investigate the morphing of electronic music through automatically applying a series of deterministic compositional transformations to the source, guided towards a target by similarity metrics. This is in contrast to other morphing techniques such as interpolation or parameters or probabilistic variation. TraSe allows control over stylistic elements of the music through user-defined weighting of numerous compositional transformations. The formal evaluation of TraSe was mostly qualitative and occurred through nine participants completing an online questionnaire. The music generated by TraSe was generally felt to be less coherent than a human composed benchmark but in some cases judged as more creative.

The educational affordances of generative media in arts education

Network Jamming systems provide real-time collaborative media performance experiences for novice or inexperienced users. In this paper we will outline the theoretical and developmental drivers for our Network Jamming software, called jam2jam. jam2jam employs generative algorithmic techniques with particular implications for accessibility and learning. We will describe how theories of engagement have directed the design and development of jam2jam and show how iterative testing cycles in numerous international sites have informed the evolution of the system and its educational potential. Generative media systems present an opportunity for users to leverage computational systems to make sense of complex media forms through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. These kinds of systems present a range of affordances that can facilitate new kinds of relationships with music and media performance and production. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences to users with little formal musical or artistic expertise.This presentation examines the educational affordances of these systems evidenced by field data drawn from the Network Jamming Project. These generative performance systems enable access to a unique kind of music/media’ ensemble performance with very little musical/ media knowledge or skill and they further offer the possibility of unique interactive relationships with artists and creative knowledge through collaborative performance. Through the process of observing, documenting and analysing young people interacting with the generative media software jam2jam a theory of meaningful engagement has emerged from the need to describe and codify how users experience creative engagement with music/media performance and the locations of meaning. In this research we observed that the musical metaphors and practices of ‘ensemble’ or collaborative performance and improvisation as a creative process for experienced musicians can be made available to novice users. The relational meanings of these musical practices afford access to high level personal, social and cultural experiences. Within the creative process of collaborative improvisation lie a series of modes of creative engagement that move from appreciation through exploration, selection, direction toward embodiment. The expressive sounds and visions made in real-time by improvisers collaborating are immediate and compelling. Generative media systems let novices access these experiences with simple interfaces that allow them to make highly professional and expressive sonic and visual content simply by using gestures and being attentive and perceptive to their collaborators. These kinds of experiences present the potential for highly complex expressive interactions with sound and media as a performance. Evidence that has emerged from this research suggest that collaborative performance with generative media is transformative and meaningful. In this presentation we draw out these ideas around an emerging theory of meaningful engagement that has evolved from the development of network jamming software. Primarily we focus on demonstrating how these experiences might lead to understandings that may be of educational and social benefit.

How can entrepreneurial musicians use electronic social networks to diffuse their music

Principal Topic: ''In less than ten years music labels will not exist anymore.'' Michael Smelli, former Global COO Sony/BMG MCA/QUT IMP Business Lab Digital Music Think Thanks 9 May 2009, Brisbane Big music labels such as EMI, Sony BMG and UMG have been responsible for promoting and producing a myriad of stars in the music industry over the last decades. However, the industry structure is under enormous threat with the emergence of a new innovative era of digital music. Recent years have seen a dramatic shift in industry power with the emergence of Napster and other file sharing sites, iTunes and other online stores, iPod and the MP3 revolution. Myspace.com and other social networking sites are connecting entrepreneurial artists with fans and creating online music communities independent of music labels. In 2008 the digital music business internationally grew by around 25% to 3.7 Billion US-Dollar. Digital platforms now account for around 20% of recorded music sales, up from 15 % in 2007 (IFPI Digital music report 2009). CD sales have fallen by 40% since their peak levels. Global digital music sales totalled an estimated US$ 3 Billion in 2007, an increase of 40% on 2006 figures. Digital sales account for an estimated 15% of global market, up from 11% in 2006 and zero in 2003. The music industry is more advanced in terms of digital revenues than any other creative or entertainment industry (except games). Its digital share is more than twice that of newspapers (7%), films (35) or books (2%). All these shifts present new possibilities for music entrepreneurs to act entrepreneurially and promote their music independently of the major music labels. Diffusion of innovations has a long tradition in both sociology (e.g. Rogers 1962, 2003) and marketing (Bass 1969, Mahajan et al., 1990). The context of the current project is theoretically interesting in two respects. First, the role of online social networks replaces traditional face-to-face word of mouth communications. Second, as music is a hedonistic product, this strongly influences the nature of interpersonal communications and their diffusion patterns. Both of these have received very little attention in the diffusion literature to date, and no studies have investigated the influence of both simultaneously. This research project is concerned with the role of social networks in this new music industry landscape, and how this may be leveraged by musicians willing to act entrepreneurially. Our key research question we intend to address is: How do online social network communities impact the nature, pattern and speed that music diffuses? Methodology/Key Propositions : We expect the nature/ character of diffusion of popular, generic music genres to be different from specialized, niche music. To date, only Moe & Fader (2002) and Lee et al. (2003) investigated diffusion patterns of music and these focus on forecast weekly sales of music CDs based on the advance purchase orders before the launch, rather than taking a detailed look at diffusion patterns. Consequently, our first research questions are concerned with understanding the nature of online communications within the context of diffusion of music and artists. Hence, we have the following research questions: RQ1: What is the nature of fan-to-fan ''word of mouth'' online communications for music? Do these vary by type of artist and genre of music? RQ2: What is the nature of artist-to-fan online communications for music? Do these vary by type of artist and genre of music? What types of communication are effective? Two outcomes from research social network theory are particularly relevant to understanding how music might diffuse through social networks. Weak tie theory (Granovetter, 1973), argues that casual or infrequent contacts within a social network (or weak ties) act as a link to unique information which is not normally contained within an entrepreneurs inner circle (or strong tie) social network. A related argument, structural hole theory (Burt, 1992), posits that it is the absence of direct links (or structural holes) between members of a social network which offers similar informational benefits. Although these two theories argue for the information benefits of casual linkages, and diversity within a social network, others acknowledge that a balanced network which consists of a mix of strong ties, weak ties is perhaps more important overall (Uzzi, 1996). It is anticipated that the network structure of the fan base for different types of artists and genres of music will vary considerably. This leads to our third research question: RQ3: How does the network structure of online social network communities impact the pattern and speed that music diffuses? The current paper is best described as theory elaboration. It will report the first exploratory phase designed to develop and elaborate relevant theory (the second phase will be a quantitative study of network structure and diffusion). We intend to develop specific research propositions or hypotheses from the above research questions. To do so we will conduct three focus group discussions of independent musicians and three focus group discussions of fans active in online music communication on social network sites. We will also conduct five case studies of bands that have successfully built fan bases through social networking sites (e.g. myspace.com, facebook.com). The idea is to identify which communication channels they employ and the characteristics of the fan interactions for different genres of music. We intend to conduct interviews with each of the artists and analyse their online interaction with their fans. Results and Implications : At the current stage, we have just begun to conduct focus group discussions. An analysis of the themes from these focus groups will enable us to further refine our research questions into testable hypotheses. Ultimately, our research will provide a better understanding of how social networks promote the diffusion of music, and how this varies for different genres of music. Hence, some music entrepreneurs will be able to promote their music more effectively. The results may be further generalised to other industries where online peer-to-peer communication is common, such as other forms of entertainment and consumer technologies.

Bayesian multinomial logit: Theory and route choice example

Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

aa-cell in practice : an approach to musical live coding

Live coding performances provide a context with particular demands and limitations for music making. In this paper we discuss how as the live coding duo aa-cell we have responded to these challenges, and what this experience has revealed about the computational representation of music and approaches to interactive computer music performance. In particular we have identified several effective and efficient processes that underpin our practice including probability, linearity, periodicity, set theory, and recursion and describe how these are applied and combined to build sophisticated musical structures. In addition, we outline aspects of our performance practice that respond to the improvisational, collaborative and communicative requirements of musical live coding.

Projecting Computational Sense of Self: A Study of Transition in a Chronic Illness Online Community

We report on analysis of discussions in an online community of people with chronic illness using socio-cognitively motivated, automatically produced semantic spaces. The analysis aims to further the emerging theory of "transition" (how people can learn to incorporate the consequences of illness into their lives). An automatically derived representation of sense of self for individuals is created in the semantic space by the analysis of the email utterances of the community members. The movement over time of the sense of self is visualised, via projection, with respect to axes of "ordinariness" and "extra-ordinariness". Qualitative evaluation shows that the visualisation is paralleled by the transitions of people during the course of their illness. The research aims to progress tools for analysis of textual data to promote greater use of tacit knowledge as found in online virtual communities. We hope it also encourages further interest in representation of sense-of-self.

Experience design and interactive software in music education research

This paper examines the integration of computing technologies into music education research in a way informed by constructivism. In particular, this paper focuses on an approach established by Jeanne Bamberger, which the author also employs, that integrates software design, pedagogical exploration, and the building of music education theory. In this tradition, researchers design software and associated activities to facilitate the interactive manipulation of musical structures and ideas. In short, this approach focuses on designing experiences and tools that support musical thinking and doing. In comparing the work of Jean Bamberger with that of the author, this paper highlights and discusses issues of significance and identifies lessons for future research.