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This Is a Title Computational Music Archiving as Physical Culture Theory Prof. Dr. Rolf Bader Institute of Systematic Musicology University of Hamburg Neue Rabenstr. 13, 20354 Hamburg, Germany [email protected] ABSTRACT: The framework of the Computational Music and Sound Archive (COMSAR) is discussed. The aim is to analyze and sort musical pieces of music from all over the world with computational tools. Its analysis is based on Music Information Retrieval (MIR) tools, the sorting algorithms used are Hidden- Markov models and self-organazing Kohonen maps (SOM). Different kinds of systematizations like taxonomies, self-organazing systems as well as bottom-up methods with physiological motivation are discussed, next to the basic signal- processing algorithms. Further implementations include musical instrument ge- ometries with their radiation characteristics as measured by microphone arrays, as well as the vibrational reconstruction of these instruments using physical model- ing. Practically the aim is a search engine for music which is based on musical pa- rameters like pitch, rhythm, tonality, form or timbre using methods close to neu- ronal and physiological mechanisms. Still the concept also suggests a culture the- ory based on physical mechanisms and parameters, and therefore omits specula- tion and theoretical overload. instruments54 as a detailed basis for such a 2 BACKGROUND classification. This classification system still 2.1 KINDS OF MUSIC SYSTEMS holds today and is only enlarged by electronic The aim of Systematic Musicology, right from musical instruments, whos development started the start around 1900, is the seek for universals in the second half of the 19th and was very prominent in the second half of the 20th in music, for rules, relations, systems or 51 interactions holding for all musical styles of all century . The success of this classification is ethnic groups and cultures around the world61. caused by its classification idea of sorting Music recordings and Phonogram Archives musical instruments according to acoustical played a crucial role for establishing the field, properties, namely their driving mechanisms. as only after the invention of the Edison So instruments can be plucked, bowed, blown phonograph for recording music on wax or struck, which produces similar timbres. This cylinders60 it was possible to compare music classification system is therefore showing a recorded by ethnomusicologists. The first of unity in the variety by comparing instruments. such archives was the Berlin Phonogram Therefore the field of Systematic Musicology in these days was called Comparative Archive established by Erich von Hornbostel 59 and Carl Stumpf with a historical recording of Musicology . Taxonomies have been applied a Thai phi pha orchestra at a visit in the Berlin in many contexts in the field. A prominent Tiergarten 1900. Many recordings followed, example is that of musical styles forming feature lists38 as applied to singing styles like those of Jaap Kunst recording music of 39 Indonesia?. around the world . 2.1.1 TAXONOMY 2.1.2 SELF-ORGANIZATION One way of giving the endless variety of Classification is a hierarchical structure with musics a system was the Hornbostel/Sachs global nodes followed by subnodes to classification of musical instruments27 in align differentiate plucked or blown instruments into with the Sachs dictionary of musical many subcategories. This is only one kind of a 60 system, and several others have been proposed. discussed. Indeed neural processing is self- One such way is describing music as a self- orgnaization and therefore many of the organized system. The sounds produced by algorithms are often only roughly related to musical instruments are showing a very simple perception50 48 49. Still this is not the main aim behaviour, the harmonicity of their overtone of such algorithms which can be seen as structures, only due to a very complex system engineering solutions to a given task and often of linear and nonlinear substructures, like perform very well. turbulence in wind instruments or the bow- string interaction of the violin family5. The Other more complex algorithms have been perception of music in the brain in neural proposed coming closer to human perception, networks is also a self-organizing process35 37 67 like self-organizing maps of the Kohonen map 68, where many neurons interact in nonlinear type35 37 67 68 . Here features of musical sounds ways to result in simple outputs, the perception are sorted in a map according to their of timbre, rhythm, melodies or musical form. similarities. Still as the map is organizing Therefore self-organization is a second system itself, no initial estimations are needed to proposed to understand musics from all around decide about the way similarity may be the world in a more differentiated way5. measured, the features of the different sounds decide about this on their own. Also 2.1.3 PSYCHOACOUSTIC BOTTOM- algorithms estimating the fractal dimension of UP PROCESS sounds show considerable relatedness both to Yet a third kind of system to understand music the processing of sound in humans as well as is often used in Musical Signal Processing and the perceptional sensation of musical density Music Information Retrieval (MIR)29 16 17. Here as a simple result to a complex computation5. algorithms investigate the digital waveform of recorded music to retrieve information from Another kind of algorithms used for such tasks this waveform, such as pitch, timbre, rhythm are Hidden Markov Models (HMM)69. Here or other psychoacoustic parameters like the temporal development of events are roughness, brightness, density or the like. predicted as the result of some hidden process. Classification of musical instruments is This process consists of the transition between performed, as well as many other tasks like a small amount of states, like musical pitches score following or Networked Music or musical instruments. The development of Performance2. Here the computer understands their appearance is modeled here as the the music and can tell a player where he is in probability of the transition of one state the score. Musicians around the world play switching into another state, so e.g. one pitch together over the internet, and the task of the followed by another one. As such transition computer is to synchronize their playing, probabilities are of statistical nature working around the restrictions of the speed of likelihoods describe the process and therefore light, delaying the transmissions. This can be the output is not fixed beforehand leaving achieved by estimating the played music of a space for arbitrariness. Still to which extend musician before it is actually played. Piano-roll these models fit human perception is under extraction is yet another such task, where the debate. computer understands typically piano music and prints a score from the sound wave file10. Yet a totally different kind of algorithm describes music production of musical 2.2 BASIC TYPES OF ALGORITHMS instruments. Physical Modeling is a set of Many of those tasks are realized by algorithms methods to produce the sound of instruments estimating a bottom-up approach to music by knowledge about the instrument geometries retrieval, where the sound file is analyzed in and the physical laws governing their terms of its spectrum or cepstrum at first which vibration9. Several stages of complexity and is then further processed using more complex simplicity exist here, from lumped models, algorithms to end up in the retrieval result29. digital waveguides or delay lines53 to whole To which extend those algorithms represent body geometries solving the differential perception of music by humans, the processes equations governing the vibrations of plates, physiologically present from the cochlear and membranes or turbulent air flow5 18. These the neural nuclei following up to the primary algorithms use the detailed geometry and solve auditory cortex and beyond is not too much the problems in a time-dependent manner, 61 resulting in very realistic sounds and finding universals in music33, understanding its estimations of vibrating frequencies, transients system, its production and perception need to or radiation. Using extreme parallel use the analysis and analysis-by-synthesis tools computation on an Field-Programmable Gate discussed above. Including all these tasks is a Array (FPGA) these geometries can be tremendous effort, still all these fields simulated in real-time42 43. Understanding the nowadays show a high degree of specialization behaviour of instruments is often achieved in a and are able to give detailed and robust results. bottom-up way by trying different models, Therefore to combine them together to an adding or leaving out geometrical details, and automatic analysis and search engine is from the comparison between the computed straightforward. and measured sound decide about how the 2.3 COMSAR AS BIG DATA SOLU- instrument works in detail. Other more simple TION models are able to show relations between musical instruments and instrument families Such automatic systems are needed in many more easily by starting with global estimations fields. The endless amount of accessible music and adding necessary features in a topdown recordings via the internet, on CDs and in way5. archives makes it practically impossible for a single researcher and even for research teams Measurements of musical instruments are also to perform these analysis by hand. Such a Big a crucial part of the understanding the Data problem needs automatic tools for instruments and their relation one to another. researchers to cope with. Additionally, the Whole body measurement techniques, like amount of methods and their complexity are so microphone arrays4, laser interferometry41 or large that it is not feasible to have one modal analysis? all give a detailed picture researcher perform all tasks. about the spatial and temporal development of the vibrations and transients of musical Also in terms of the 'buzz' the internet instruments. High-speed cameras and subpixel produces in terms of the endless variety of tracking analysis show the movement of musics, research and consumer demands, strings or reeds45.
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