Schüler, Nico

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Symposium Computeranwendu!).gen in der Musikwissenschaft. Konzepte, Methoden, Resultate Nico Schüler On Methods and Methodology of (Computer-Assisted) Music Analysis Music analysis is very often practiced and taught without reflecting on the method used. One ofthe very few methodological writings in this area published by Wolfgang Horn (1996) points out that analysis is not possible without language and concepts. If "pure" cognition of composition does not exist, then practicing analysis and teaching analytical methods must include some reflection on its purposes. Music analysis is not an independent discipline, nor is it an activity to be defined once and for all. Rather, music analysis is a method in the original and emphatic sense of the term, which means it is a way to a goal, a means to an end. One (f i r s t) way to handle these problems of music analysis is to reflect on differ-ent methods; methods of music analysis need to be classified and described. While this task is partly done for "traditional" methods of music analysis (e. g., by Hermann Beck 1974, Diether de Ja Motte 1987, and Jonathan Dunsby & Arnold Whittall 1988), comparisons are still lacking for new ( especially computer-assisted) music analytical methods. (An exception is, certainly, Ian Bent's monograph Analysis from 1987.) Also, a c r i t i ca l evaluation is urgently needed. So, why - in more detail - is a rather methodological approach to music analysis necessary? This question must be answered with some more theoretical considera-tions. For Wolfgang Horn (1996, 12), analysis is, first ofall, neither a doctrine nor a the-ory. lt is not a formal-logical activity, but it has to do with the application of concepts to objects of experiences. And this is the reason why it is so hard to reveal it. As a nomen actionis, the term "analyzing" is singular. This activity is further explained by objects, which are supposed to be resolved "into simpler constituent elements" (Bent 1987, 1 ), and by the manne r of resolving. Using this word as a nomen acti, an a I y s i s, it is possible to forma plural: an a I y s es. (See Horn 1996, 12) But what is "music analysis" supposed to resolve? Ian Bent's definition just quoted here, continues: "Music analysis is the resolution of a musical structure into rela-tively simpler constituent elements, and the investigation of the functions of those elements within that structure." (Bent 1987, 1) But the "resolution of a musical structure" into "constituent elements" is not the resolution of an unk n o w n object, Nico Schiller: On Methods and Methodology of (Computer-Assisted) Music Analysis 381 but of an i n t er n a 1 i z e d ex per i e n c e . Acoustical events, or their notation, func-tion as a result of experiences and concepts. (Horn 1996, 12) Results of analytical resolutions are usually communicated via language. Here, language rules need to be applied. The product, the analytical text, can be verified with the help of logic. Also important, the choice of the concepts on which the analy-sis will be based, needs to be in conformation with the goals of the analysis. The (logical) terminologic-conceptional frame is most crucial. Wolfgang Horn distinguishes between two main approaches possible: the first would be answering the question "Ho w i s t h i s d o n e ? " ; the second one answers the question " Wh a t i s t h i s ? ". "The results have, in both cases, only illustrating character, because the theory 'k n o w s ' concepts" but you a p p 1 y concepts, but within a frame regarding this specific object. These kinds of analyses are important in historical research for getting an overview, but it is rather cataloging and typologiz-ing. Generally, analyses are dependent on their frame: "Only if the frame of an analy-sis is discovered, can you ask for the relevance of the analysis, e v e n if it is only the relevance for your current subjective interest." (Ibid., 13) Conclusion: Analyzing music should not only be done "right" and "logically," but the framework of the analysis needs to be j u s t i f i e d . "We should not only talk about analysis, but also, and especially, about its terms and conditions!" (Ibid., 14) Reflections on the framework of music analysis, its purposes, and its goals are most important, which t h e n require the application of certain methods. Classifications of Music Analysis can be done with regard to the music analyzed, the methods used, the general approach taken, etc. Any classification needs to be based on a logical framework, that means, a certain classificational level has to be on the same epistemological level. Dieter de Ja Motte, for instance, distinguishes the fol-lowing analytical categories: a) Large Fonn --+ Detail Structure b) Measure-by-Measure Analysis c) Analysis ofa Word-Tone-Composition d) Category Analysis e) Comparative Analysis f) Special Analysis g) Tendency Analysis h) Statistical Analysis i) Analytical Details j) Analysis with no Prerequisites Here, different epistemological levels are mixed, like musical categories (e. g., form, structure), kind of music (word-tone-composition), certain methods (statistics), etc. Jan Bent, on the other band, is with his analytical categories within the same epis-temological level, since he only aims at specific theories. To support that notion, he mentions the author of each theory in parentheses: a) Fundamental Structure (Schenker) b) Thematic Process (Reti) and Functional Analysis (Keller) c) Fonnal Analysis d) Phrase-Structure Analysis (Riemann) 382 Symposium: Computeranwendungen in der Musikwissenschaft e) Category and Feature Analysis (Lomax; LaRue) f) Musical Semiotics (Ruwet and Nattiez) g) Information Theory h) Set Theory However, if he would really want to regard to each specific theory, his list is far too short and eclectic. Other theories would have to be added: different theories of harmony, melody, rhythm, and so on. For this reason, another classificational system of music analysis with regard to musical elements, at which the analysis is aimed, shall be suggested here: a) Form Analysis b) Melodie Analysis Thematic Analysis Motivic Analysis Phrase Structure Analysis c) Harmonie Analysis d) Contrapuntal Analysis e) Rhythmic Analysis f) Analysis of Word-Tone-Relations g) Analysis of Instrumentation Each of these categories can be sub-divided (indicated here already for "melodic analysis"). Musical categories as range, type of motion, certain pattems, timbre, tex-ture, sound, etc. are included. To classify with regard to the approach used - always depending on the goal ofthe analysis - the following categories could be distinguished: a) Schenkerian Analysis b) Transformational Grammar Analysis c) Comparative Analysis d) Measure-by-Measure Analysis e) Statistical Analysis f) Information Theoretical Analysis g) Semiotical Analysis h) Category and Feature Analysis i) Cognitive and Al Analysis j) Process Analysis This list is certainly not complete. In some of these categories, specific theories are implied; however, since these are very broad and established analysis areas, a classifi-cation under "analytical approaches" seems to be justified. An additional sub-category could distinguish between the basis of the analysis: whether it is notational based or performance based (i. e. is the object to be analyzed notated music or performed mu-sic ). Another classification would be possible within the epistemological level "kind of presentation" of the analysis. Here, de la Motte's "Special Analysis" would fit in, which is - in the beginning - not supposed to reveal what the analysis will to show, but will have a surprising result in the end. However, there are so many different kinds of presentation possible that a classification in this respect does not seem ap-propriate. The more interesting question would be if there is a classificational system possible with regard to g o a 1 s of analyses, since this is the ultimate aim of any ana-Nico Schüler: On Methods and Methodo/ogy of (Computer-Assisted) Music Analysis 383 lytical work. This, coupled with the unification of these different classification levels in o n e model, remains for further researcb. A separate point addresses the use of technology for music analysis. All analytical methods can be supported by the use of computers, which leads to the main topic of this symposium. Computer-assisted music analysis provides analytical tools to help solving problems which cannot be solved with traditional methods of music analysis. For instance, it clarifies stylistic characterizations and questions of unclear authorship, it helps investigating musical (historical) developments, and it is useful for further developments of theoretical systems, for acoustical and performance research, as well as for cognitive and artificial intelligence research. Introductory reading materials for the history of computer-assisted music analysis, such as overview articles by Bo Alphonce (1980, 1989) present only the 'tip of the iceberg' of these approaches; dozens of dissertations and numerous American as weil as European articles are excluded. Also, most articles fail to reflect on the subject critically. More specifically, they do not show the limits of these applications. Thus, early applications, for instance, are not complex enough and without using enough musical material to support their findings . To rephrase this problem: From today's point of view, the first approaches seem relatively simplistic, strongly emphasizing the computer more so than the m u s i c re-search. They usually dealt with only a few compositions, or single voice melodies, or even with short phrases of single voices, and this strongly effected the outcome of the research and its acadernic value. However, the simplistic nature of the research was mainly determined by the capacities of the computers in these early years. Negative evaluations of computer-assisted music analysis in the 1960s and 1970s were then re-sponsible for reservations against computer applications in music research. A classificational system of methods of computer-assisted music analysis could be outlined as follows: Statistical & Information-Theoretical Analyses Set Theoretical Analyses Other Mathematical Analyses Hierarchical Analyses Transformational Analyses Schenkerian Analyses Spectral Analyses Cognitive & Al Analyses Combined Analyses Each of these categories can be subdivided into "notation-based" and "perform-ance based." Finally, these applications can be distinguished with regard to the kind ofmusic: Western Art Music Not Western Art Music Western Folk Music Non-Western Music Non-Western Art Music Non-Western Folk Music Pop/ Jazz Music 384 Symposium: Computeranwendungen in der Musikwissenschaft Tbus, tbe classification model for computer-assisted music analysis suggested bere comprises three different (epistemological) abtraction levels: 1. Methods Used 2. Kind ofRepresentation ofthe Music 3. Kind ofMusic Corning back to tbe problem of bistorizing computer-assisted approacbes of music analysis on the one band and classifying tbose on tbe other leads to the main episte-mological problem. Even tbougb of a sbort bistory, computer-assisted music analysis bas been developing in a variety of streams, under a variety of metbodical prerequi-sites. For tbat reason, it is almost impossible to talk about a real "bistory" of com-puter-assisted music analysis. Ratber, approacbes of computer-assisted music analysis bas to be seen within the classificational system of their metbods given above. On the otber band, tbe development of tbe classificational system was only possible after a thorougb study of all existing approacbes; bere, bistorical aspects play an important role also. For tbe reason of lack of space, bistorical remarks bave to be omitted bere. How-ever, a brief outline is given in the appendix. Instead, tbese reflections bere will be limited to conclusions of tbe study of computer-assisted music analysis: First Conclusion A critical thinking needs to be establisbed. Beyond the eupboria of tbe use of technol-ogy, only a few computer-assisted music analysis applications bave made important contributions so far. Even with tbe newest cognitive and AI researcb, tbe proportion of expenditure to benefit is in most cases unsatisfactory. Second Conclusion The productive use of elementary statistical and information-tbeoretical measure-ments (frequencies and resulting probabilities, entropies, etc.) seems tobe independ-ent ofthe musical genre. More complex analyses in tbe sense of interactive methods -comprising traditional, sociological, psycbological and historic-cultural aspects -sbow that, for certain goals, neitber a pure 'traditional' nor a pure statistical analysis will bring valuable results . Instead, computer-assisted music analysis needs to use both computational an d traditional analytical metbods - certainly always dependent on the general goal of tbe analysis. Third Conclusion Using metbods derived from linguistics, theories of structural levels, and set tbeory, computer-assisted music analysis is based on 'traditional' music tbeory - in the sense of studying musical structures. Tbe computer makes it possible to verify tbe results / algorithms by using tbe reverse process, syntbesizing tbe composing. Fourth Conlcusion Finally, computer-assisted music analysis in tbe field of Artificial Intelligence is mucb more interdisciplinary. Especially tbe strong integration of psycbological and cogni-Nico Schüler: On Methods and Methodology of (Computer-Assisted) Music Analysis 385 tive aspects of music perception allows one to focus on basic human activities, the creation of knowledge as weil as processes of composition and perception. With this, it focuses more on the question: How can I know, or how can I discover, myself and the world? Literature Bo H. Alphonce: Music Analysis by Computer - A Field for Theory Formation, in: Computer Music Journal 4 (1980) 2, pp. 26-35. ---: Computer Applications: Analysis and Modeling, in: Music Theory Spectrum 11 (1989) 1, pp. 49-59. Hermann Beck: Methoden der Werkanalyse in Geschichte und Gegenwart, 3. Aufl ., Wilhelmsha-ven 1981. !an D. Bent: Analysis, with a Glossary by W. Drabkin, London 1987. Diether de la Motte: Musikalische Analyse, Kassel 1987. Johnathan Dunsby & Arnold Whittall : Music Analysis in Theory and Practice, London 1988. Wolfgang Horn: Satzlehre, Musiktheorie, Analyse. Variationen über ein ostinates Thema, in: Zum Problem und zu Methoden von Musikanalyse, ed. by Nico Schüler, Hamburg 1996, pp. 11-31. Nico Schüler: Zum Problem und zu Methoden computerunterstützter Musikanalyse, Magister-thesis, Greifswald University 1995 . ---: Methoden computerunterstützter Musikanalyse - ein historischer Überblick, in: Zum Problem und zu Methoden von Musikanalyse, ed. by Nico Schüler, Hamburg 1996, pp. 51-76. Appendix: History of Computer-Assisted Music Analysis - Outline 1941 first functioning electro-mechanic computer by Konrad Zuse 1946 first fully electronic computer ("ENIAC") by John P. Eckert and John Mouchly 1949 Bertrand Bronson used an electronic calculator to effectivate a typologizing procedure with British-American ballads 1949 Claude E. Shannon defined "entropy" 1958 first statistical and information theoretical analyses of art music by Willhelm Fucks 1960 first American dissertation by Joseph E. Youngblood on information-theoretical analysis of mu-sic 1960s foundation of"Information Aesthetics" by Max Bense and Abraham A. Moles 1964 first American dissertation with an actual use ofa computer, by Gilbert H. Roller 1966 following Bart6k, Alica Elschekova developed computer-assisted methods of Analysis and clas-sification offolk songs 1968 first !arger study on classification and typologies of folk songs, including analyses of similarity, by Reiner Kluge 1968 first American dissertation on computer-assisted set theoretical analyses by Donald M. Pederson 1970s foundation of"Cognitive Musicology" by Otto Laske 1971 first computational study in the area of structural levels in music by John E. Rothgeb 1974 computational foundation of set theory by Bo Alphonce 1974 first dissertation in the area of Artificial Intelligence by Denis L. Baggi 1977 first personal computers: the Apple II 1980 discussions on a system for computer-assisted Schenkerian Analysis 1982 first computer-assisted analysis of Jazz by James K. Williams 1995 psycho-acoustical AI model for tone center recognition by Mark Leman 1997 start of the !arge "Music, Mind, Machine" project by Peter Desain and Henkjan Honing at the Nijmegen Institute for Cognition and Information 

On Methods and Methodology of (Computer-Assisted) Music Analysis

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On Methods and Methodology of (Computer-Assisted) Music Analysis

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