Thematische Bibliographien / Computer music / Zeitschriftenartikel
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Zeitschriftenartikel zum Thema „Computer music“

Autor: Grafiati
Veröffentlicht am 4. Juni 2021
Zuletzt aktualisiert am 12. Oktober 2024

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1

Owens, Robert J., Laszlo Dubrovay, Ricardo Mandolini und Tamas Ungvary. „Computer Music“. Computer Music Journal 13, Nr. 1 (1989): 65. http://dx.doi.org/10.2307/3679860.

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2

Schüler, Nico. „Reflections on the History of Computer-Assisted Music Analysis I: Predecessors and the Beginnings“. Musicological Annual 41, Nr. 1 (01.12.2005): 31–43. http://dx.doi.org/10.4312/mz.41.1.31-43.

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This article is the first of a series that focuses on the history of computer-assisted music analysis. This first article discusses the philosophical basis of computer-assisted music analysis, i.e. the application of information theory to aesthetics, as well as representative applications of statistical and information-theoretical measurements to music analysis and other computational approaches to music analysis that did not include the use of electronic computers. In most cases, those approaches were direct models for computer-assisted applications. Finally, this article provides a short historical account of the development of early computers and summarizes the earliest computer-applications to music analysis, carried out during the 1950s.
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3

Dannenberg, Roger B., Nicolas E. Gold, Dawen Liang und Guangyu Xia. „Methods and Prospects for Human–Computer Performance of Popular Music“. Computer Music Journal 38, Nr. 2 (Juni 2014): 36–50. http://dx.doi.org/10.1162/comj_a_00238.

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Computers are often used in performance of popular music, but most often in very restricted ways, such as keyboard synthesizers where musicians are in complete control, or pre-recorded or sequenced music where musicians follow the computer's drums or click track. An interesting and yet little-explored possibility is the computer as highly autonomous performer of popular music, capable of joining a mixed ensemble of computers and humans. Considering the skills and functional requirements of musicians leads to a number of predictions about future human–computer music performance (HCMP) systems for popular music. We describe a general architecture for such systems and describe some early implementations and our experience with them.
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4

Rowe, Robert, Barlow, Dashow, Kaske, Lansky, Roads und Waisvisz. „New Computer Music“. Computer Music Journal 14, Nr. 3 (1990): 83. http://dx.doi.org/10.2307/3679967.

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5

Mailer, Albert, M. Bagella, N. Sani, S. Tamburini, G. Nottoli und F. Galante. „Computer Music Concerto“. Computer Music Journal 15, Nr. 2 (1991): 80. http://dx.doi.org/10.2307/3680924.

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6

Gresham-Lancaster, Scot. „Computer Music Network“. Leonardo 47, Nr. 3 (Juni 2014): 266–67. http://dx.doi.org/10.1162/leon_a_00771.

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The social climate and cultural atmosphere of the San Francisco Bay Area in the late 70's early 80's plus the emergence of the nascent microcomputer industry made for a social network and approach that fostered the creation of a new type of collaborative electronic music ensemble with techniques that have come to be known as “Computer Music Network”. A transformation from initial heterogeneous to a more homogeneous underlying paradigm has brought with it aesthetic questions about the reason and evolution of this new genre.
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7

Rudi, Jøran. „Computer music animations“. Organised Sound 3, Nr. 3 (Dezember 1998): 193–98. http://dx.doi.org/10.1017/s1355771898003033.

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Electroacoustic music, since its inception, has been situated in a cross-disciplinary no-man's-land, with areas of interest spread in many directions; from ideas of musical structures ordered through traditional pitch-classes to research on physical modelling and analysis of sound and compositional structures through the use of neural networks. Much of the material found in computer music has been developed through processes of appropriation, both from sound recordings of physical events and from the application of various principles found in the natural sciences.
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8

Wilmink, Jan. „Computer music I“. Microprocessing and Microprogramming 24, Nr. 1-5 (August 1988): 433. http://dx.doi.org/10.1016/0165-6074(88)90091-9.

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9

Cuypers, L. „Computer music programming“. Microprocessing and Microprogramming 25, Nr. 1-5 (Januar 1989): 65–69. http://dx.doi.org/10.1016/0165-6074(89)90175-0.

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10

Kiraly, Zsuzsanna. „Solfeggio 1: A Vertical Ear Training Instruction Assisted by the Computer“. International Journal of Music Education os-40, Nr. 1 (Mai 2003): 41–58. http://dx.doi.org/10.1177/025576140304000105.

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The aim of this paper is to describe the process of solfège learning when assisted by computers. The research was conducted in the Länsi-Uusimaa Music Institute in Finland. The study focused on pupils’ attitudes, opinions, motivation, and learning-outcomes using computer-based music learning. We also examined how Solfeggio 1, the new electronic ear-training material, works. Jukka Louhivuori (1990) has examined the didactical questions of computer-assisted music education. He emphasized that learning music with a computer does not mean the replacement of “real” music. The notions of learning and teaching can change in quality, mainly in the area of “learning-by-doing” and “discovery learning” in the computer-assisted music classroom. It was found that computer-assisted music learning is more agreeable and effective than traditional music learning. Although results showed that we need a well-functioning, modern environment and a well-educated “researcher-teacher,” well-motivated pupils are the most important aspects.
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11

Larrieu, Maxence. „A Consideration of the Code of Computer Music as Writing, and Some Thinking on Analytical Theories“. Organised Sound 24, Nr. 3 (29.11.2019): 319–28. http://dx.doi.org/10.1017/s1355771819000384.

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This article focuses on the analysis of computer music, that is, music which uses programming languages so that what the listener hears is the result of computer code. One key point in this article is that this music exists with some writing, that is, the computer code. I note that this key point has not been addressed in the latest theories for analysing computer music. Indeed, we often see this music as part of the electroacoustic field, where the audio signal is essential, and where we usually read that those musics are non-written music. After an introduction on this topic, in the second section I will make a distinction between ‘before the signal’ and ‘from the signal’ to organise the theories to analyse electroacoustic music. In the third section, I will focus on computer music and I will show the historical difficulty in considering ‘code’ in musical analysis, mainly with an important exchange between two pioneers, Marco Stroppa and Jean-Claude Risset. In the fourth section I will explain with Jean-Claude Risset and Horacio Vaggione the specificity of computer music: this music is written. Finally, I will look into a recent analysis theory, the Interactive Aural Analysis by Michael Clarke, which seems to fit with the latter specificity.
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12

Schüler, Nico. „Reflections on the History of Computer-Assisted Music Analysis II: The 1960s“. Musicological Annual 42, Nr. 1 (01.12.2006): 5–24. http://dx.doi.org/10.4312/mz.42.1.5-24.

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This article, the second in a series of articles on the history of computer-assisted music analysis, focuses on developments of computer-assisted music analysis during the 1960s. While the most trendsetting approaches and publications are being discussed, this article points out that at least up to the end of the 1960s, computer-assisted analysis of style was anything but comprehensive, interpersonal, and rich in musical insight. Nevertheless, the wealth of attempts to analyze music with the help of computers during the 1960s provided the foundation for the deeper approaches to computer-assisted music analysis of the following decades.
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13

Fumarola, Martin Alejandro. „Computer Music Library: Editor's Note in "Computer Music Journal" 17(3)“. Computer Music Journal 19, Nr. 4 (1995): 8. http://dx.doi.org/10.2307/3680985.

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14

Pople, Anthony. „Computer music and computer-based musicology“. Computers & Education 19, Nr. 1-2 (Juli 1992): 173–82. http://dx.doi.org/10.1016/0360-1315(92)90023-x.

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15

OSAKA, NAOTOSHI. „New prospects of music brought about by Computers. New Music Creation by Computer.“ Journal of the Institute of Electrical Engineers of Japan 120, Nr. 1 (2000): 23–26. http://dx.doi.org/10.1541/ieejjournal.120.23.

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16

Kim-Boyle, David. „International Computer Music Conference 2005: Music Review“. Computer Music Journal 30, Nr. 2 (Juni 2006): 87–90. http://dx.doi.org/10.1162/comj.2006.30.2.87.

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17

Schüler, Nico. „From Musical Grammars to Music Cognition in the 1980s and 1990s: Highlights of the History of Computer-Assisted Music Analysis“. Musicological Annual 43, Nr. 2 (01.12.2007): 371–96. http://dx.doi.org/10.4312/mz.43.2.371-396.

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While approaches that had already established historical precedents – computer-assisted analytical approaches drawing on statistics and information theory – developed further, many research projects conducted during the 1980s aimed at the development of new methods of computer-assisted music analysis. Some projects discovered new possibilities related to using computers to simulate human cognition and perception, drawing on cognitive musicology and Artificial Intelligence, areas that were themselves spurred on by new technical developments and by developments in computer program design. The 1990s ushered in revolutionary methods of music analysis, especially those drawing on Artificial Intelligence research. Some of these approaches started to focus on musical sound, rather than scores. They allowed music analysis to focus on how music is actually perceived. In some approaches, the analysis of music and of music cognition merged. This article provides an overview of computer-assisted music analysis of the 1980s and 1990s, as it relates to music cognition. Selected approaches are being discussed.
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18

Rastruba, T., und K. Kushnir. „USE OF MODERN MUSIC AND COMPUTER TECHNOLOGIES IN THE DISCIPLINE STUDY «CHORAL ARRANGEMENT»“. Research Notes, Nr. 1 (04.05.2022): 76–83. http://dx.doi.org/10.31654/2663-4902-2022-pp-1-76-83.

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Modernization of the education system of Ukraine involves changing the content of the training process for future professionals in the field of computer music. Taking into account the specifics of the training of music teachers, the approach to the choice of modern educational tools is changing. This allows us to emphasize the features of professional music education in Ukraine. The urgency of this topic is due to the widespread use of computers in modern music and pedagogical practice, a significant amount of scientific work in the field of theory of computer technology and its insufficient use in the educational and creative process of students of higher education institutions. The aim of this article is to reveal and analyze modern approaches to the use and application of music and computer technology in the study of choral arrangement and their important impact on the quality of training of future music teachers. The article describes the stages of learning that take place in the study of the discipline «Choral Arrangement» and focuses on the need to introduce innovative approaches, methods, forms and teaching aids using different types of technical means, namely: computer, synthesizer, electronic textbooks, Internet technologies and modern music and computer programs. An important place in the analytical review of the literature was occupied by published materials on the use of computer technology in music education. An analysis of the main research and publications on this issue, as well as the authors’ own observations, led to the conclusion that the use of modern music and computer technology is essential in choral arranging classes. Activation of students’ independent work in performing choral arrangements with the help of computer programs «Music Editor» and computer music programs for recording, processing and arranging choral works helps to intensify learning and interest of students in their future profession.
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19

Lyon, Eric. „A Computer Music Retrospective“. Organised Sound 13, Nr. 3 (03.11.2008): 209–16. http://dx.doi.org/10.1017/s1355771808000307.

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AbstractA composer who has worked in the field of computer music for the last 25 years reflects on how technological developments during that time have affected his work in computer music, instrumental music and hybrid combinations of the two. The compositional trajectories traced here often run parallel to opportunities afforded by the evolution of computer technology suitable for the generation of digital audio.
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20

Syarif, Arry Maulana, Azhari Azhari, Suprapto Suprapto und Khafiizh Hastuti. „Human and Computation-based Music Representation for Gamelan Music“. Malaysian Journal Of Music 9 (20.11.2020): 82–100. http://dx.doi.org/10.37134/mjm.vol9.7.2020.

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A public database containing representative data of karawitan traditional music is needed as a resource for researchers who study computer music and karawitan. To establish this database, a text-based pitch model for music representation that is both human and computer-based was first investigated. A new model of musical representation that can be read by humans and computers is proposed to support music and computer research on karawitan also known as gamelan music. The model is expected to serve as the initial effort to establish a public database of karawitan music representation data. The proposed model was inspired by Helmholtz Notation and Scientific Pitch Notation and well-established, text-based pitch representation systems. The model was developed not only for pitch number, high or low or middle pitch information (octave information), but for musical elements found in gamelan sheet music pieces that include pitch value and legato signs. The model was named Gendhing Scientific Pitch Notation (GSPN). Ghending is a Javanese word that means “song”. The GSPN model was designed to represent music by formulating musical elements from a sheet music piece. Furthermore, the model can automatically be converted to other music representation formats. In the experiment, data in the GSPN format was implemented to automatically convert sheet music to a binary code with localist representation technique.
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21

Charrieras, Damien, und François Mouillot. „Getting Out of the Black Box: analogising the use of computers in electronic music and sound art“. Organised Sound 20, Nr. 2 (07.07.2015): 191–99. http://dx.doi.org/10.1017/s1355771815000072.

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The process of creating computer-based music is increasingly being conceived in terms of complex chains of mediations involving composer/performer and computer software interactions that prompt us to reconsider notions of materiality within the context of digital cultures. Recent scholarship has offered particularly useful re-evaluations of computer music software in relation to musical instrumentality. In this article, we contend that given the ubiquitous presence of computer units within contemporary musical practices, it is not simply music software that needs to be reframed as musical instruments, but rather the diverse material strata of machines identified as computers that need to be thought of as instruments within music environments. Specifically, we argue that computers, regardless of their technical specifications, are not only ‘black boxes’ or ‘meta-tools’ that serve to control music software, but are also material objects that are increasingly being used in a wide range of musical and sound art practices according to an ‘analog’ rather than ‘digital’ logic. Through a series of examples implicating both soft and hard dimensions of what constitutes computers, we provide a preliminary survey of practices calling for the need to rethink the conceptual divide between analog and digital forms of creativity and aesthetics.
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22

Arici, Ismet. „The Relationship Between the Music Teacher Candidates’ Computer-Assisted Teaching Attitudes and Exam Anxiety in Computer Literacy“. Journal of Education and Training Studies 6, Nr. 11 (17.10.2018): 215. http://dx.doi.org/10.11114/jets.v6i11.3696.

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Today, improving instructional technologies have increased at a significant pace particularly with the introduction of computers in education. Computers have contributed greatly to every field of education. Computers have supported the preparation of powerful audio-visual materials with multiple-media features and have also empowered the education sector with the software options intended for different fields. Consequently; computer-assisted education (CAE) has come into its own.As the use of computers has become widespread and computers have found an important place in education, attitudes about computer-assisted education have become important, as well. Particularly the empowerment of the attitudes of teacher candidates, as the educators of the future, toward computer-assisted education, is a significant gain for education.Computer literacy lessons provided for in education faculties are significant in that they may help teacher candidates to prepare computer-assisted education materials and to use computers effectively in education process.Finding out whether the attitudes toward computer-assisted education have positive impact on exam anxiety in computer lessons, analysing the factors which determine the attitudes, and understanding the reasons for anxiety will be useful in carrying out new researchers in order to make significant contributions to education processes.This research included 46 teacher candidates studying Computer-Assisted Music Teaching in the Department of Music Teaching Education at Marmara University. The students completed the exam anxiety inventory and CAE attitude scale prior to administration of the computer-assisted music education exam. The results of the research indicated a significant negative relationship between the students’ CAE attitude levels and their anxiety levels. Findings of the scales showed that, CAE attitudes were high and anxiety levels were low. Findings of the study indicated that the computer education they received contributed positively to their computer experiences and their attitudes towards CAE.
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23

Fowler, Michael. „Music Printing by Computer“. Musical Times 129, Nr. 1745 (Juli 1988): 335. http://dx.doi.org/10.2307/964742.

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Maverick, Vance, und F. Richard Moore. „Elements of Computer Music“. Leonardo Music Journal 1, Nr. 1 (1991): 110. http://dx.doi.org/10.2307/1513134.

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25

Gerzso, Andrew. „Paradigms and Computer Music“. Leonardo Music Journal 2, Nr. 1 (1992): 73. http://dx.doi.org/10.2307/1513212.

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26

Pinzarrone, Joseph. „Computer Music in China“. Computer Music Journal 11, Nr. 3 (1987): 9. http://dx.doi.org/10.2307/3679732.

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27

Hammer, Ernest Lee, und Peter Manning. „Electronic and Computer Music“. Computer Music Journal 12, Nr. 2 (1988): 54. http://dx.doi.org/10.2307/3679942.

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28

Rowe, Robert, Mario Davidovsky, Gottfried Michael Koenig, Denis Lorrain, Emmanuel Ghent, Daniel Arfib und Loren Rush. „Computer Music Currents 2“. Computer Music Journal 15, Nr. 1 (1991): 62. http://dx.doi.org/10.2307/3680390.

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29

Blevins, R. L., und Deta Davis. „Computer Music Bibliography Supplement“. Computer Music Journal 18, Nr. 2 (1994): 105. http://dx.doi.org/10.2307/3680450.

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30

Rowe, Robert, David Evan Jones, Michel Decoust, Charles Dodge, Jean-Baptiste Barriere, Trevor Wishart und Roger Reynolds. „Computer Music Currents 4“. Computer Music Journal 16, Nr. 4 (1992): 95. http://dx.doi.org/10.2307/3680474.

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31

Rowe, Robert, Francois Bayle, Richard Karpen, William Schottstaedt und Johannes Goebel. „Computer Music Currents 3“. Computer Music Journal 16, Nr. 1 (1992): 92. http://dx.doi.org/10.2307/3680499.

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32

Rowe, Robert, Denis Smalley, Mesias Maiguashca, Gareth Loy, Kaija Saariaho und Jonathan Harvey. „Computer Music Currents 5“. Computer Music Journal 17, Nr. 1 (1993): 75. http://dx.doi.org/10.2307/3680576.

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33

Snell, John, und F. Richard Moore. „Elements of Computer Music“. Computer Music Journal 14, Nr. 4 (1990): 67. http://dx.doi.org/10.2307/3680793.

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34

Rowe, Robert, Savouret, Lindwall und Oppenheim. „Computer Music Currents 1“. Computer Music Journal 14, Nr. 4 (1990): 73. http://dx.doi.org/10.2307/3680798.

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35

Nelson, James. „State of Computer Music“. Computer Music Journal 20, Nr. 3 (1996): 4. http://dx.doi.org/10.2307/3680810.

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36

Harris, Craig. „Concert of Computer Music“. Computer Music Journal 15, Nr. 4 (1991): 98. http://dx.doi.org/10.2307/3681085.

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37

Loop, Dwight. „Airplay for Computer Music“. Computer Music Journal 21, Nr. 1 (1997): 11. http://dx.doi.org/10.2307/3681208.

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38

McCabe, Donna, und Christopher K. Koenigsberg. „Brains-Audiophile Computer Music“. Computer Music Journal 20, Nr. 1 (1996): 115. http://dx.doi.org/10.2307/3681284.

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39

Berger, Jonathan, Curtis Roads und John Strawn. „Foundation of Computer Music“. Journal of Music Theory 31, Nr. 2 (1987): 331. http://dx.doi.org/10.2307/843715.

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40

Mallinckrodt, A. John, und Peter Manning. „Electronic and Computer Music“. Leonardo 21, Nr. 2 (1988): 210. http://dx.doi.org/10.2307/1578564.

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41

K., R., Curtis Roads und John Strawn. „Foundations of Computer Music“. Notes 43, Nr. 1 (September 1986): 53. http://dx.doi.org/10.2307/897845.

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42

Tanguiane, Andranick. „Soviet Computer Music Center“. Computer Music Journal 10, Nr. 2 (1986): 7. http://dx.doi.org/10.2307/3679479.

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43

Rothstein, Joseph. „Yamaha C1 Music Computer“. Computer Music Journal 13, Nr. 4 (1989): 93. http://dx.doi.org/10.2307/3679563.

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44

Loy, D. Gareth, Curtis Roads und John Strawn. „Foundations of Computer Music“. Computer Music Journal 9, Nr. 3 (1985): 80. http://dx.doi.org/10.2307/3679578.

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45

Ostertag, Bob. „Human Bodies, Computer Music“. Leonardo Music Journal 12 (Dezember 2002): 11–14. http://dx.doi.org/10.1162/096112102762295070.

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46

Lindblom, ke. „Computer in music education“. Education and Computing 4, Nr. 3 (Januar 1988): 157–59. http://dx.doi.org/10.1016/s0167-9287(88)80004-9.

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47

Loubet, Emmanuelle. „International Computer Music Festival“. Computer Music Journal 23, Nr. 2 (Juni 1999): 88–93. http://dx.doi.org/10.1162/comj.1999.23.2.88.

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48

Land, Michael. „International Conference on Computer Music and Music Science“. Computer Music Journal 21, Nr. 3 (1997): 97. http://dx.doi.org/10.2307/3681018.

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49

Wallace, F. Layne, und Yap Siong Chua. „Teaching computer music in a computer setting“. Computers & Education 21, Nr. 4 (November 1993): 337–43. http://dx.doi.org/10.1016/0360-1315(93)90037-j.

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50

Yan, Baihui, und Qiao Zhou. „Music Learning Based on Computer Software“. International Journal of Emerging Technologies in Learning (iJET) 12, Nr. 12 (20.12.2017): 142. http://dx.doi.org/10.3991/ijet.v12i12.7961.

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In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teachers have not found a reasonable countermeasure to them. Against this background, the introduction of computer music software to music learning is a new trial that can not only cultivate the students’ initiatives of music learning, but also enhance their abilities to learn music. Therefore, it is concluded that the computer software based music learning is of great significance to improving the current music learning modes and means.
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