By David Meredith
This publication presents an in-depth advent and evaluation of present learn in computational tune research. Its seventeen chapters, written via best researchers, jointly characterize the variety in addition to the technical and philosophical sophistication of the paintings being performed this present day during this intensely interdisciplinary box. A vast diversity of techniques are offered, applying thoughts originating in disciplines reminiscent of linguistics, info thought, info retrieval, trend attractiveness, computer studying, topology, algebra and sign processing. the various equipment defined draw on well-established theories in track concept and research, reminiscent of Forte's pitch-class set idea, Schenkerian research, the equipment of semiotic research constructed through Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative idea of Tonal tune. The ebook is split into six components, masking methodological concerns, harmonic and pitch-class set research, shape and voice-separation, grammars and hierarchical relief, motivic research and trend discovery and, ultimately, class and the invention of unique styles. As an in depth and updated photo of present examine in computational tune research, the e-book offers a useful source for researchers, academics and scholars in song thought and research, desktop technology, song details retrieval and similar disciplines. It additionally offers a cutting-edge reference for practitioners within the tune know-how undefined.
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Extra info for Computational Music Analysis
To display this conception of analysis in graphical form, an additional arrow is required to show the crucial additional input to the analytical process, input which generally comes from the analyst herself or himself (Fig. 6). I suspect most analysts follow this interpretative conception of analysis, even when they write as if they are revealing a structure intrinsic to the piece. (Perhaps Piece ★✥ ★✥ ★✥ ★✥ ✤✜✎ ✍ ✲ ✣✢ ✧✦ ✧✦ ✧✦ ✧✦ Fig. ) Certainly this is how most analyses are used by their readers.
5’: A study in semiological music analysis. Music Analysis, 1(3):243–340. -J. (1990). Music and Discourse: Towards a Semiology of Music. Princeton University Press. Pauwels, J. -P. (2014). Combining musicological knowledge about chords and keys in a simultaneous chord and local key estimation system. Journal of New Music Research, 43(3):318–330. Pearce, M. and Wiggins, G. (2012). Auditory expectation: The information dynamics of music perception and cognition. Topics in Cognitive Science, 4(4):625–652.
2007). Computing pitch names in tonal music: A comparative analysis of pitch spelling algorithms. PhD thesis, Faculty of Music, University of Oxford. Meredith, D. (2012). Music analysis and Kolmogorov complexity. In Proceedings of the 19th Colloquio di Informatica Musicale (XIX CIM), Trieste, Italy. 28 Alan Marsden Meredith, D. (2015). Music analysis and point-set compression. Journal of New Music Research, 44(3). In press. -J. (1982). 5’: A study in semiological music analysis. Music Analysis, 1(3):243–340.
Computational Music Analysis by David Meredith