UNIVERSITY of CALIFORNIA, IRVINE Algorithmic Improvisers
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Peter Johnston 2011
The London School Of Improvised Economics - Peter Johnston 2011 This excerpt from my dissertation was included in the reader for the course MUS 211: Music Cultures of the City at Ryerson University. Introduction The following reading is a reduction of a chapter from my dissertation, which is titled Fields of Production and Streams of Conscious: Negotiating the Musical and Social Practices of Improvised Music in London, England. The object of my research for this work was a group of musicians living in London who self-identified as improvisers, and who are part of a distinct music scene that emerged in the mid-1960s based on the idea of free improvisation. Most of this research was conducted between Sept 2006 and June 2007, during which time I lived in London and conducted interviews with both older individuals who were involved in the creation of this scene, and with younger improvisers who are building on the formative work of the previous generation. This chapter addresses the practical aspects of how improvised music is produced in London, and follows a more theoretical analysis in the previous chapters of why the music sounds like it does. Before moving on to the main content, it will be helpful to give a brief explanation of two of the key terms that occur throughout this chapter: “free improvisation” and the “improvised music field.” “Free improvisation” refers to the creation of musical performances without any pre- determined materials, such as form, tonality, melody, or rhythmic feel. This practice emerged out of developments in jazz in the late 1950s and early 1960s, particularly in the work of Ornette Coleman and Cecil Taylor, who began performing music without using the song-forms, harmonic progressions, and steady rhythms that characterized jazz until that time. -
Some Notes on John Zorn's Cobra
Some Notes on John Zorn’s Cobra Author(s): JOHN BRACKETT Source: American Music, Vol. 28, No. 1 (Spring 2010), pp. 44-75 Published by: University of Illinois Press Stable URL: http://www.jstor.org/stable/10.5406/americanmusic.28.1.0044 . Accessed: 10/12/2013 15:16 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp . JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. University of Illinois Press is collaborating with JSTOR to digitize, preserve and extend access to American Music. http://www.jstor.org This content downloaded from 198.40.30.166 on Tue, 10 Dec 2013 15:16:53 PM All use subject to JSTOR Terms and Conditions JOHN BRACKETT Some Notes on John Zorn’s Cobra The year 2009 marks the twenty-fifth anniversary of John Zorn’s cele- brated game piece for improvisers, Cobra. Without a doubt, Cobra is Zorn’s most popular and well-known composition and one that has enjoyed remarkable success and innumerable performances all over the world since its premiere in late 1984 at the New York City club, Roulette. Some noteworthy performances of Cobra include those played by a group of jazz journalists and critics, an all-women performance, and a hip-hop ver- sion as well!1 At the same time, Cobra is routinely played by students in colleges and universities all over the world, ensuring that the work will continue to grow and evolve in the years to come. -
Discovering the Neuroanatomical Correlates of Music with Machine Learning
Discovering the Neuroanatomical Correlates of Music with Machine Learning In Eduardo Reck Miranda (Eds.). Handbook of Artificial Intelligence for Music. Part 1. Springer Tatsuya Daikoku 1 International Research Center for Neurointelligence, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 2 Centre for Neuroscience in Education, Department of psychology, University of Cambridge, Cambridge, United Kingdom [email protected] Please cite as: Daikoku T. Discovering the Neuroanatomical Correlates of Music with Machine Learning. In Eduardo Reck Miranda (Eds.). Handbook of Artificial Intelligence for Music. Part 1. Springer (in press). 6.1 Introduction 1 Music is ubiquitous in our lives yet unique to humans. The interaction between music and the brain is complex, engaging a variety of neural circuits underlying sensory perception, learning and memory, action, social communication, and creative activities. Over the past decades, a growing body of literature has revealed the neural and computational underpinnings of music processing including not only sensory perception (e.g., pitch, rhythm, and timbre), but also local/non-local structural processing (e.g., melody and harmony). These findings have also influenced Artificial Intelligence and Machine Learning systems, enabling computers to possess human-like learning and composing abilities. Despite the plenty of evidence, more study is required for complete account of music knowledge and creative mechanisms in human brain. This chapter reviews the neural correlates of unsupervised learning with regard to the computational and neuroanatomical architectures of music processing. Further, we offer a novel theoretical perspective on the brain’s unsupervised learning machinery that considers computational and neurobiological constraints, highlighting the connections between neuroscience and machine learning. -