Chapter 1: Lerdahl's Model of Tonal Pitch Space
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Melodies in Space: Neural Processing of Musical Features A
Melodies in space: Neural processing of musical features A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Roger Edward Dumas IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Dr. Apostolos P. Georgopoulos, Adviser Dr. Scott D. Lipscomb, Co-adviser March 2013 © Roger Edward Dumas 2013 Table of Contents Table of Contents .......................................................................................................... i Abbreviations ........................................................................................................... xiv List of Tables ................................................................................................................. v List of Figures ............................................................................................................. vi List of Equations ...................................................................................................... xiii Chapter 1. Introduction ............................................................................................ 1 Melody & neuro-imaging .................................................................................................. 1 The MEG signal ................................................................................................................................. 3 Background ........................................................................................................................... 6 Melodic pitch -
Fourier Phase and Pitch-Class Sum
Fourier Phase and Pitch-Class Sum Dmitri Tymoczko1 and Jason Yust2(B) Author Proof 1 Princeton University, Princeton, NJ 08544, USA [email protected] 2 Boston University, Boston, MA 02215, USA [email protected] AQ1 Abstract. Music theorists have proposed two very different geometric models of musical objects, one based on voice leading and the other based on the Fourier transform. On the surface these models are completely different, but they converge in special cases, including many geometries that are of particular analytical interest. Keywords: Voice leading Fourier transform Tonal harmony Musical scales Chord geometry· · · · 1Introduction Early twenty-first century music theory explored a two-pronged generalization of traditional set theory. One prong situated sets and set-classes in continuous, non-Euclidean spaces whose paths represented voice leadings, or ways of mov- ing notes from one chord to another [4,13,16]. This endowed set theory with a contrapuntal aspect it had previously lacked, embedding its discrete entities in arobustlygeometricalcontext.AnotherpronginvolvedtheFouriertransform as applied to pitch-class distributions: this provided alternative coordinates for describing chords and set classes, coordinates that made manifest their harmonic content [1,3,8,10,19–21]. Harmonies could now be described in terms of their resemblance to various equal divisions of the octave, paradigmatic objects such as the augmented triad or diminished seventh chord. These coordinates also had a geometrical aspect, similar to yet distinct from voice-leading geometry. In this paper, we describe a new convergence between these two approaches. Specifically, we show that there exists a class of simple circular voice-leading spaces corresponding, in the case of n-note nearly even chords, to the nth Fourier “phase spaces.” An isomorphism of points exists for all chords regardless of struc- ture; when chords divide the octave evenly, we can extend the isomorphism to paths, which can then be interpreted as voice leadings. -
Generalized Tonnetze and Zeitnetz, and the Topology of Music Concepts
June 25, 2019 Journal of Mathematics and Music tonnetzTopologyRev Submitted exclusively to the Journal of Mathematics and Music Last compiled on June 25, 2019 Generalized Tonnetze and Zeitnetz, and the Topology of Music Concepts Jason Yust∗ School of Music, Boston University () The music-theoretic idea of a Tonnetz can be generalized at different levels: as a network of chords relating by maximal intersection, a simplicial complex in which vertices represent notes and simplices represent chords, and as a triangulation of a manifold or other geomet- rical space. The geometrical construct is of particular interest, in that allows us to represent inherently topological aspects to important musical concepts. Two kinds of music-theoretical geometry have been proposed that can house Tonnetze: geometrical duals of voice-leading spaces, and Fourier phase spaces. Fourier phase spaces are particularly appropriate for Ton- netze in that their objects are pitch-class distributions (real-valued weightings of the twelve pitch classes) and proximity in these space relates to shared pitch-class content. They admit of a particularly general method of constructing a geometrical Tonnetz that allows for interval and chord duplications in a toroidal geometry. The present article examines how these du- plications can relate to important musical concepts such as key or pitch-height, and details a method of removing such redundancies and the resulting changes to the homology the space. The method also transfers to the rhythmic domain, defining Zeitnetze for cyclic rhythms. A number of possible Tonnetze are illustrated: on triads, seventh chords, ninth-chords, scalar tetrachords, scales, etc., as well as Zeitnetze on a common types of cyclic rhythms or time- lines. -
Interactive Music System Based on Pitch Quantization and Tonal Navigation
Interactive music system based on pitch quantization and tonal navigation Leonardo Aldrey MASTER’S THESIS UPF / 2011 Master in Sound and Music Computing September 3, 2011 Sergi Jordà Puig - Supervisor Department of Information and Communication Technologies Universitat Pompeu Fabra, Barcelona 1 Abstract Recent developments in the field of human computer interaction have led to new ways of making music using digital instruments. The new set of sensors available in devices such as smartphones and touch tablets propose an interesting challenge in the field of music technology regarding how they can be used in a meaningful and musical way. One to one control over parameters such as pitch, timbre and amplitude is no longer required thus making possible to play music at a different level of abstraction. Lerdahl and Jackendoff presented in their publication “Generative theory of tonal music” a perspective that combines Heinrich Schenker’s theory of music and Noam Chomsky linguistics to eXplain how tonal music is organized and structured. This idea opens up the possibility of investigating ways to manipulate a “wider” aspect of music through an assisted interactive musical system that takes into account the “principles” or common knowledge used in music composition and performance. Numerous publications exist in the field of music theory regarding how the tonal aspect of music works. Due to aspects related to psychoacoustics and cultural inheritance, there is a certain common base on how to form and use chords and scales, and how they are organized in terms of hierarchies, movement tendencies and tonal functions. This project deals with the design of a graphical representation about the use of tonality in jazz and popular music, organizing chords and scales in a hierarchical, semanticall and practical way. -
A Multi-Level Tonal Interval Space for Modelling Pitch Relatedness and Musical Consonance
Journal of New Music Research, 2016 Vol. 45, No. 4, 281–294, http://dx.doi.org/10.1080/09298215.2016.1182192 A multi-level tonal interval space for modelling pitch relatedness and musical consonance Gilberto Bernardes1 ,DiogoCocharro1,MarceloCaetano1 ,CarlosGuedes1,2 and Matthew E.P. Davies1 1INESC TEC, Portugal; 2New York University Abu Dhabi, United Arab Emirates (Received 12 March 2015; accepted 18 April 2016) Abstract The intelligibility and high explanatory power of tonal pitch spaces usually hide complex theories, which need to account In this paper we present a 12-dimensional tonal space in the for a variety of subjective and contextual factors. To a certain context of the ,Chew’sSpiralArray,andHarte’s Tonnetz extent, the large number of different, and sometimes con- 6-dimensional Tonal Centroid Space. The proposed Tonal tradictory, tonal pitch spaces presented in the literature help Interval Space is calculated as the weighted Discrete Fourier us understand the complexity of such representations. Exist- Transform of normalized 12-element chroma vectors, which ing tonal spaces can be roughly divided into two categories, we represent as six circles covering the set of all possible pitch each anchored to a specific discipline and applied methods. intervals in the chroma space. By weighting the contribution On the one hand we have models grounded in music theory of each circle (and hence pitch interval) independently, we (Cohn, 1997, 1998;Lewin,1987;Tymoczko,2011; Weber, can create a space in which angular and Euclidean distances 1817–1821), and on the other hand, models based on cogni- among pitches, chords, and regions concur with music theory tive psychology (Krumhansl, 1990;Longuet-Higgins,1962; principles. -
The Tonal Diffusion Model.Transactions of the International Society for Music Information Retrieval,3(1), Pp
Lieck, R., et al. (2020). The Tonal Diffusion Model.Transactions of the International Society for Music Information Retrieval,3(1), pp. 7,60,5 153–164. DOI: https://doi.org/10.5334/tismir.46 RESEARCH The Tonal Diffusion Model Robert Lieck, Fabian C. Moss and Martin Rohrmeier Pitch-class distributions are of central relevance in music information retrieval, computational musicology and various other fields, such as music perception and cognition. However, despite their structure being closely related to the cognitively and musically relevant properties of a piece, many existing approaches treat pitch-class distributions as fixed templates. In this paper, we introduce the Tonal Diffusion Model, which provides a more structured and interpretable statistical model of pitch-class distributions by incorporating geometric and algebraic structures known from music theory as well as insights from music cognition. Our model explains the pitch-class distributions of musical pieces by assuming tones to be generated through a latent cognitive process on the Tonnetz, a well-established representation for harmonic relations. Specifically, we assume that all tones in a piece are generated by taking a sequence of interval steps on the Tonnetz starting from a unique tonal origin. We provide a description in terms of a Bayesian generative model and show how the latent variables and parameters can be efficiently inferred. The model is quantitatively evaluated on a corpus of 248 pieces from the Baroque, Classical, and Romantic era and describes the empirical pitch-class distributions more accurately than conventional template-based models. On three concrete musical examples, we demonstrate that our model captures relevant harmonic characteristics of the pieces in a compact and interpretable way, also reflecting stylistic aspects of the respective epoch. -
Interval Vectors
Ilhan M. Izmirli George Mason University [email protected] The exploration of the profound and intrinsic cohesion between mathematics and music is certainly nothing new – it actually dates all the way back to Pythagoras (c. 570 BCE – c. 495 BCE). However, the introduction of the dodecaphonic (twelve-tone) system developed by Arnold Schoenberg (1874 – 1951) has taken this study to entirely new levels, and has instituted such concepts as set theory, ordered sets, vectors, and various types of spaces as useful tools in music theory. In this paper we will look into one of these tools, namely the notion of interval vectors. Around 1908, the Viennese composer Arnold Schoenberg developed a system of pitch organization in which all twelve unique pitches were to be arranged into an ordered row. This row and the rows obtained from it by various basic operations were then used to generate entire pitch contents, giving rise to a method of composition now usually referred to as the dodecaphonic (twelve-tone) system or serialism. This new system not only bolstered the existing ties between mathematics and music, but helped introduce some new ones as well. In fact, the field of musical set theory was developed by Hanson (1960) and Forte (1973) in an effort to categorize musical objects and describe their relationships in this new setting. For more information see Schuijer (2008) and Morris (1987). Let us first review the basic terminology, starting with a notational convention. We will call the octave from middle 퐶 to the following 퐵 the standard octave. If 퐶 denotes the middle 퐶, we will use the convention 퐶 = 0. -
A Unified Helical Structure in 3D Pitch Space for Mapping Flat Musical Isomorphism
HEXAGONAL CYLINDRICAL LATTICES: A UNIFIED HELICAL STRUCTURE IN 3D PITCH SPACE FOR MAPPING FLAT MUSICAL ISOMORPHISM A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science University of Regina By Hanlin Hu Regina, Saskatchewan December 2015 Copytright c 2016: Hanlin Hu UNIVERSITY OF REGINA FACULTY OF GRADUATE STUDIES AND RESEARCH SUPERVISORY AND EXAMINING COMMITTEE Hanlin Hu, candidate for the degree of Master of Science in Computer Science, has presented a thesis titled, Hexagonal Cylindrical Lattices: A Unified Helical Structure in 3D Pitch Space for Mapping Flat Musical Isomorphism, in an oral examination held on December 8, 2015. The following committee members have found the thesis acceptable in form and content, and that the candidate demonstrated satisfactory knowledge of the subject material. External Examiner: Dr. Dominic Gregorio, Department of Music Supervisor: Dr. David Gerhard, Department of Computer Science Committee Member: Dr. Yiyu Yao, Department of Computer Science Committee Member: Dr. Xue-Dong Yang, Department of Computer Science Chair of Defense: Dr. Allen Herman, Department of Mathematics & Statistics Abstract An isomorphic keyboard layout is an arrangement of notes of a scale such that any musical construct has the same shape regardless of the root note. The mathematics of some specific isomorphisms have been explored since the 1700s, however, only recently has a general theory of isomorphisms been developed such that any set of musical intervals can be used to generate a valid layout. These layouts have been implemented in the design of electronic musical instruments and software applications. -
Geometric and Transformational
GENERIC (MOD-7) GEOMETRIC AND TRANSFORMATIONAL APPROACHES TO VOICE LEADING IN TONAL MUSIC Leah Frederick Submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree Doctor of Philosophy in the Jacobs School of Music, Indiana University May 2020 Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Doctoral Committee ______________________________________ Julian Hook, Ph.D. Research Director ______________________________________ Richard Cohn, Ph.D. ______________________________________ Andrew Mead, Ph.D. ______________________________________ Christopher Raphael, Ph.D. ______________________________________ Frank Samarotto, Ph.D. April 10, 2020 ii Copyright © 2020 Leah Frederick iii ACKNOWLEDGEMENTS There has been perhaps no better time than now, in our socially distanced society of April 2020, to acknowledge the individuals and communities who have provided support and encouragement over the past few years. First and foremost, I wish to thank my advisor, Jay Hook, for his meticulous attention to detail, for his mentorship on navigating academia, and for sharing his enthusiasm of both music and mathematics. Perhaps more than any of those, however, I’m grateful for the encouragement and confidence that he has offered during the many moments when I’ve doubted myself. I also wish to recognize the rest of my dissertation committee, Rick Cohn, Andy Mead, Frank Samarotto, and Chris Raphael, for their willingness to serve on my committee and for their helpful feedback. I further extend gratitude to the entire music theory faculty at Indiana University. During my four years in Bloomington, each and every faculty member contributed to shaping my values and ways of thinking about music. -
TUE Coding Rules
Ein Beitrag zur tonraumbasierten Analyse und Synthese musikalischer Audiosignale Dissertation zur Erlangung des akademischen Grades Doktoringenieur (Dr.-Ing.) vorgelegt der Fakultät für Elektrotechnik und Informationstechnik der Technischen Universität Ilmenau von Dipl.-Ing. Gabriel Gatzsche, geboren am 21.05.1979 in Bad Langensalza von Dipl.-Ing. Markus Mehnert, geboren am 23.01.1976 in Hünfeld Gutachter: Prof. Dr.-Ing. Dr. rer. nat. h.c. Karlheinz Brandenburg Prof. Dr.-Ing. Thomas Sporer Prof. Thomas Krämer vorgelegt am: 25.05.2009 Verteidigung am: 29.04.2011 Verf.-Nr.: EI 240 urn:nbn:de:gbv:ilm1-2011000164 ZUSAMMENFASSUNG Zusammenfassung Das Ziel dieser Arbeit besteht darin, Verbesserungen in der Analyse und Synthese von Audiosig- nalen durch Anwendung von Tonräumen zu erreichen. Im ersten Teil, der die Kapitel 2 bis 6 enthält und von Gabriel Gatzsche verfasst wurde, erfolgt die mathematisch-geometrische Beschreibung der Tonalität auf verschiedenen hierarchischen Ebenen angelehnt an Fred Lerdahls Tonal Pitch Space, David Gatzsches Kadenzkreis und Elaine Chew’s Spiral Array (Berechnung von geometrischen Schwerpunkten in Tonraummodellen). Mit Hilfe zweier Formeln, der Symmetriemodell-Generatorformel und dem SYM-Operator, wird es möglich, die Entstehung der wichtigsten Hauptebenen der abendländischen Tonalität aus einer Quintreihe zu beschreiben, verschiedene, auf eine Tonart bezogene Modelle zu erzeugen und auf den jeweili- gen Symmetrieton zu zentrieren. Damit gelingt es, eine Vielzahl bereits existierender Modelle zu verbinden und in ein einheitliches als Symmetriemodell bezeichnetes Framework zu integrieren. Um auch reale Musiksignale tonraumbasiert analysieren zu können, wird mit dem Summenvektor im kreisförmigen Tonraum ein Feature-Vektor vorgestellt, der wichtige tonale Eigenschaften eines Musiksignals niedrigdimensional repräsentiert. Dazu gehören z.B. funktionstheoretische Eigen- schaften, das Tongeschlecht, Spannungs- und Auflösungsbestreben oder auch harmonische Mehr- deutigkeiten. -
The Geometry of Tonal Space
BRIDGES Mathematical Connections in Art, Mnsic, and Science Hearing With Our Eyes: The Geometry of Tonal Space Julian L. Hook School of Music Penn State University University Park, PA 16802-1901 E-mail: [email protected] There is no intrinsic reason why musical structures should be represented graphically. Music is, after aU, an auditory phenomenon. It consists of vibrations transmitted through the air as sound waves, received by our ears and processed by our brains as acoustic data. Visual aspects of music-the arrangement of musicians on a stage or of notes on a page, the gyrations of the conductor, the shine of the piano-are of secondary importance in our understanding and appreciation of a musical work. Most human beings, however, are visually oriented. We rely on our eyes more than our ears or any of our other sense organs in finding our way around, identifying other people and objects, and learning new information. Because of this dependence on the visual world, most people find abstract concepts easier to grasp if they can somehow be visualized: if some sort of graphical, geometric representation can be devised showing, if only metaphorically, the important elements of the conceptual framework and their relationships with each other. Even if these elements exist in sound and time rather than in light and space, such a representation may help us to get our bearings and to interpret what we hear. Pitches, chords, and key areas are examples of musical elements that lend themselves well to graphical depiction. Many music theorists through the centuries have drawn diagrams showing the appearance of "tonal space" from various perspectives. -
Inversion in Music Jonathan Dimond, Phd
INTRODUCTION TO INVERSION IN MUSIC JONATHAN DIMOND, PHD C B C# A# D A D# G# E G F F# Edition: December, 2020 INTRODUCTION ..............................................................................................3 Terminology and enquiry ...........................................................................................4 INVERSION IN PITCH SPACE ...........................................................................7 INVERSION IN PITCH REGISTER ....................................................................13 INVERSION IN PITCH-CLASS SPACE ...............................................................15 Comparison of inversion in pitch space, register and pitch-class space ........................19 INVERSION IN RHYTHM ...............................................................................22 CONCLUSION ...............................................................................................29 BIBLIOGRAPHY .............................................................................................30 C B C# A# D A D# G# E G F F# INTRODUCTION Inversion is a concept that is found broadly within the musical fields of music theory, counterpoint, harmony, composition, aural training, notation, and the practice of musical instruments. It is based upon the over-arching concept of symmetry – a trait found in all the arts.1 This paper aims to alert the musician of the multitude of interpretations of the term inversion, to amalgamate different approaches and terminology into one reference document, as well as to