Set Theory: a Gentle Introduction Dr
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Surviving Set Theory: a Pedagogical Game and Cooperative Learning Approach to Undergraduate Post-Tonal Music Theory
Surviving Set Theory: A Pedagogical Game and Cooperative Learning Approach to Undergraduate Post-Tonal Music Theory DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Angela N. Ripley, M.M. Graduate Program in Music The Ohio State University 2015 Dissertation Committee: David Clampitt, Advisor Anna Gawboy Johanna Devaney Copyright by Angela N. Ripley 2015 Abstract Undergraduate music students often experience a high learning curve when they first encounter pitch-class set theory, an analytical system very different from those they have studied previously. Students sometimes find the abstractions of integer notation and the mathematical orientation of set theory foreign or even frightening (Kleppinger 2010), and the dissonance of the atonal repertoire studied often engenders their resistance (Root 2010). Pedagogical games can help mitigate student resistance and trepidation. Table games like Bingo (Gillespie 2000) and Poker (Gingerich 1991) have been adapted to suit college-level classes in music theory. Familiar television shows provide another source of pedagogical games; for example, Berry (2008; 2015) adapts the show Survivor to frame a unit on theory fundamentals. However, none of these pedagogical games engage pitch- class set theory during a multi-week unit of study. In my dissertation, I adapt the show Survivor to frame a four-week unit on pitch- class set theory (introducing topics ranging from pitch-class sets to twelve-tone rows) during a sophomore-level theory course. As on the show, students of different achievement levels work together in small groups, or “tribes,” to complete worksheets called “challenges”; however, in an important modification to the structure of the show, no students are voted out of their tribes. -
The Social Economic and Environmental Impacts of Trade
Journal of Modern Education Review, ISSN 2155-7993, USA August 2020, Volume 10, No. 8, pp. 597–603 Doi: 10.15341/jmer(2155-7993)/08.10.2020/007 © Academic Star Publishing Company, 2020 http://www.academicstar.us Musical Vectors and Spaces Candace Carroll, J. X. Carteret (1. Department of Mathematics, Computer Science, and Engineering, Gordon State College, USA; 2. Department of Fine and Performing Arts, Gordon State College, USA) Abstract: A vector is a quantity which has both magnitude and direction. In music, since an interval has both magnitude and direction, an interval is a vector. In his seminal work Generalized Musical Intervals and Transformations, David Lewin depicts an interval i as an arrow or vector from a point s to a point t in musical space. Using Lewin’s text as a point of departure, this article discusses the notion of musical vectors in musical spaces. Key words: Pitch space, pitch class space, chord space, vector space, affine space 1. Introduction A vector is a quantity which has both magnitude and direction. In music, since an interval has both magnitude and direction, an interval is a vector. In his seminal work Generalized Musical Intervals and Transformations, David Lewin (2012) depicts an interval i as an arrow or vector from a point s to a point t in musical space (p. xxix). Using Lewin’s text as a point of departure, this article further discusses the notion of musical vectors in musical spaces. t i s Figure 1 David Lewin’s Depiction of an Interval i as a Vector Throughout the discussion, enharmonic equivalence will be assumed. -
The Generalised Hexachord Theorem
THEOREM OF THE DAY The Generalised Hexachord Theorem Suppose that S is a subset of the set of pitch classes comprising Zn, n even, with |S | = s; then the interval class vectors of S and its complement Zn \ S differ component- wise by |n − 2s|, except for the last component, for which the difference is |n/2 − s|. The interval class vector of S is the vector of length n/2 whose i-th component is the number of pairs a, b ∈ S , a < b, for which min(b − a, n − b + a) = i. For Z12, the integers modulo 12, this is illustrated above, using the opening bars of Chopin’s op. 10, no. 5, for i = 5 (the upper, red, curves in bars 2–3) and i = 2 (the lower, green, curves). The word ‘class’ is used to indicate that no distinction is made between the interval from, say, B♭ down to E♭ (the first red curve) or from B♭ up to E♭; both intervals have value 5 = min(10 − 3, 12 − 10 + 3). The complete interval class vectors have been calculated here using David Walters’ PC Set Calculator, which is attached to Gary Tucker’s excel- lent Introduction to Pitch Class Analysis. The right-hand part of Chopin’s ´etude uses only the five black-key notes of the piano, the complement of this set being all the white keys. The Generalised Hexachord Theorem then tells us that components 1–5 of the corresponding interval classes differ uniformly by 12 − 2 × 5 = 2. The original Hexachord Theorem, due to the composer Milton Babbitt and theorist David Lewin in the 1950s, applies to subsets of exactly six notes out of the twelve note scale, the interval class vectors of this ‘hexachord’ or ‘hexad’ and its complement then being identical. -
The Computational Attitude in Music Theory
The Computational Attitude in Music Theory Eamonn Bell Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Eamonn Bell All rights reserved ABSTRACT The Computational Attitude in Music Theory Eamonn Bell Music studies’s turn to computation during the twentieth century has engendered particular habits of thought about music, habits that remain in operation long after the music scholar has stepped away from the computer. The computational attitude is a way of thinking about music that is learned at the computer but can be applied away from it. It may be manifest in actual computer use, or in invocations of computationalism, a theory of mind whose influence on twentieth-century music theory is palpable. It may also be manifest in more informal discussions about music, which make liberal use of computational metaphors. In Chapter 1, I describe this attitude, the stakes for considering the computer as one of its instruments, and the kinds of historical sources and methodologies we might draw on to chart its ascendance. The remainder of this dissertation considers distinct and varied cases from the mid-twentieth century in which computers or computationalist musical ideas were used to pursue new musical objects, to quantify and classify musical scores as data, and to instantiate a generally music-structuralist mode of analysis. I present an account of the decades-long effort to prepare an exhaustive and accurate catalog of the all-interval twelve-tone series (Chapter 2). This problem was first posed in the 1920s but was not solved until 1959, when the composer Hanns Jelinek collaborated with the computer engineer Heinz Zemanek to jointly develop and run a computer program. -
Pitch-Class Sets and Microtonalism Hudson Lacerda (2010)
Pitch-class sets and microtonalism Hudson Lacerda (2010) Introduction This text addresses some aspects of pitch-class sets, in an attempt to apply the concept to equal-tempered scales other than 12-EDO. Several questions arise, since there are limitations of application of certain pitch-class sets properties and relations in other scales. This is a draft which sketches some observations and reflections. Pitch classes The pitch class concept itself, assuming octave equivalence and alternative spellings to notate the same pitch, is not problematic provided that the interval between near pitches is enough large so that different pitches can be perceived (usually not a problem for a small number of equal divisions of the octave). That is also limited by the context and other possible factors. The use of another equivalence interval than the octave imposes revere restrictions to the perception and requires specially designed timbres, for example: strong partials 3 and 9 for the Bohlen-Pierce scale (13 equal divisions of 3:1), or stretched/shrinked harmonic spectra for tempered octaves. This text refers to the equivalence interval as "octave". Sometimes, the number of divisions will be referred as "module". Interval classes There are different reduction degrees: 1) fit the interval inside an octave (13rd = 6th); 2) group complementar (congruent) intervals (6th = 3rd); In large numbers of divisions of the octave, the listener may not perceive near intervals as "classes" but as "intonations" of a same interval category (major 3rd, perfect 4th, etc.). Intervals may be ambiguous relative to usual categorization: 19-EDO contains, for example, an interval between a M3 and a P4; 17-EDO contains "neutral" thirds and so on. -
Reducing Pessimism in Interval Analysis Using Bsplines Properties: Application to Robotics∗
Reducing Pessimism in Interval Analysis using BSplines Properties: Application to Robotics∗ S´ebastienLengagne, Universit´eClermont Auvergne, CNRS, SIGMA Cler- mont, Institut Pascal, F-63000 Clermont-Ferrand, France. [email protected] Rawan Kalawouny Universit´eClermont Auvergne, CNRS, SIGMA Cler- mont, Institut Pascal, F-63000 Clermont-Ferrand, France. [email protected] Fran¸coisBouchon CNRS UMR 6620 and Clermont-Auvergne University, Math´ematiquesBlaise Pascal, Campus des C´ezeaux, 3 place Vasarely, TSA 60026, CS 60026, 63178 Aubi`ere Cedex France [email protected] Youcef Mezouar Universit´eClermont Auvergne, CNRS, SIGMA Cler- mont, Institut Pascal, F-63000 Clermont-Ferrand, France. [email protected] Abstract Interval Analysis is interesting to solve optimization and constraint satisfaction problems. It makes possible to ensure the lack of the solu- tion or the global optimal solution taking into account some uncertain- ties. However, it suffers from an over-estimation of the function called pessimism. In this paper, we propose to take part of the BSplines prop- erties and of the Kronecker product to have a less pessimistic evaluation of mathematical functions. We prove that this method reduces the pes- simism, hence the number of iterations when solving optimization or con- straint satisfaction problems. We assess the effectiveness of our method ∗Submitted: December 12, 2018; Revised: March 12, 2020; Accepted: July 23, 2020. yR. Kalawoun was supported by the French Government through the FUI Program (20th call with the project AEROSTRIP). 63 64 Lengagne et al, Reducing Pessimism in Interval Analysis on planar robots with 2-to-9 degrees of freedom and to 3D-robots with 4 and 6 degrees of freedom. -
Geometrical Music Theory
Clifton Callender College of Music, Florida State University. Ian Quinn Music Department, Yale University. Dmitri Tymoczko Music Department, Princeton University. To whom correspondence should be addressed. All three authors contributed equally to this report. GENERALIZED VOICE-LEADING SPACES SUMMARY: We translate basic concepts of music theory into the language of contemporary geometry. ABSTRACT: Western musicians traditionally classify pitch sequences by disregarding the effects of five musical transformations: octave shift, permutation, transposition, inversion, and cardinality change. Here we model this process mathematically, showing that it produces 32 equivalence relations on chords, 243 equivalence relations on chord sequences, and 32 families of geometrical quotient spaces, in which both chords and chord-sequences are represented. This model reveals connections between music- theoretical concepts, yields new analytical tools, unifies existing geometrical representations, and suggests a way to understand similarity between chord-types. To interpret music is to ignore information. A capable musician can understand the sequence of notes (C4, E4, G4) in various ways: as an ordered pitch sequence (an “ascending C-major arpeggio starting on middle C”), an unordered collection of octave- free note-types (a “C major chord”), an unordered collection of octave-free note-types modulo transposition (a “major chord”), and so on. Musicians commonly abstract away from five types of information: the octave in which notes appear, their order, their specific pitch level, whether a sequence appears “rightside up” or “upside down” (inverted), and the number of times a note appears. Different purposes require different information; consequently, there is no one optimal degree of abstraction. Here we model this process. -
Euromac 9 Extended Abstract Template
9th EUROPEAN MUSIC ANALYSIS CONFERENC E — E U R O M A C 9 Scott Brickman University of Maine at Fort Kent, USA [email protected] Collection Vectors and the Octatonic Scale (013467), 6z23 (023568), 6-27 (013469), 6-30 (013679), ABSTRACT 6z49 (013479) and 6z50 (014679). Background 6z13 transforms to 6z50 under the M7 operation. 6z23 and 6z49 Allen Forte, writing in The Structure of Atonal Music (1973), map unto themselves under the M7 operation, as do 6-27 and tabulated the prime forms and vectors of pitch-class sets 6-30 whose compliments are themselves. (PCsets). Additionally, he presented the idea of a set-complex, a set of sets associated by virtue of the inclusion relation. So, a way to perceive these hexachords is that they provide five Post-Tonal Theorists such as John Rahn, Robert Morris and areas. Joseph Straus, allude to Forte’s set-complex, but do not treat the concept at length. The interval vector, developed by Donald Martino, tabulates the intervals (dyads) in a collection. In order to comprehend the The interval vector, developed by Donald Martino (“The Source constitution of the octatonic hexachords, I decided to create a Set and Its Aggregate Formations,” Journal of Music Theory 5, "collection vector" which would tabulated the trichordal, no. 2, 1961) is a means by which the intervals, and more tetrachordal and pentachordal subsets of each octatonic specifically the dyads contained in a collection, can be identified hexachord. and tabulated. I began exploring the properties of the OH by tabulating their There exists no such tool for the identification and tabulation of trichordal subsets. -
Composing with Pitch-Class Sets Using Pitch-Class Sets As a Compositional Tool
Composing with Pitch-Class Sets Using Pitch-Class Sets as a Compositional Tool 0 1 2 3 4 5 6 7 8 9 10 11 Pitches are labeled with numbers, which are enharmonically equivalent (e.g., pc 6 = G flat, F sharp, A double-flat, or E double-sharp), thus allowing for tonal neutrality. Reducing pitches to number sets allows you to explore pitch relationships not readily apparent through musical notation or even by ear: i.e., similarities to other sets, intervallic content, internal symmetries. The ability to generate an entire work from specific pc sets increases the potential for creating an organically unified composition. Because specific pitch orderings, transpositions, and permutations are not dictated as in dodecaphonic music, this technique is not as rigid or restrictive as serialism. As with integral serialism, pc numbers may be easily applied to other musical parameters: e.g., rhythms, dynamics, phrase structure, sectional divisions. Two Representations of the Matrix for Schönberg’s Variations for Orchestra a. Traditional method, using pitch names b. Using pitch class nomenclature (T=10, E=11) Terminology pitch class — a particular pitch, identified by a name or number (e.g., D = pc 2) regardless of registral placement (octave equivalence). interval class (ic) — the distance between two pitches expressed numerically, without regard for spelling, octave compounding, or inversion (e.g., interval class 3 = minor third or major sixth). pitch-class set — collection of pitches expressed numerically, without regard for order or pitch duplication; e.g., “dominant 7th” chord = [0,4,7,10]. operations — permutations of the pc set: • transposition: [0,4,7,10] — [1,5,8,11] — [2,6,9,0] — etc. -
Introduction to Pitch Class Set Analysis Pitch Class - a Pitch Without Regard to Its Octave Position
Theory 3 Dr. Crist Introduction to Pitch Class Set Analysis Pitch Class - A pitch without regard to its octave position. There are twelve total pitch classes. There is only one pitch class (C) represented here. Pitch Class Set - A group of pitch classes. Usually it isa motive that occurs melodically, harmonically, or both. Cardinal number refers to the number of elements in a set. A cardinal three set has three members. Octave Equivalence - In tonal music, if two notes an octave apart are presented we attribute them to the same tonal significance. When we hear a chord with widely spaced notes we recognize it as an expanded form of a closed position chord. Removal of redundant pitch classes. C Major Inversional Equivalence - When a chord changes its position (inversion) we recognize it as being the same chord. Even though these two chords are in different positions, both are still tonic functions. I6 I Transpositional Equivalence - In tonal music, when a pattern of notes transposes to another pitch level its identity is retained. Though the keys are different, one hears the chord functions as being equivalent. I IV V7 I = I IV V7 I Segmentation - The procedure for determining which musical units of a composition are to be regarded as analytical objects. Consider all musical parameters (register, duration, timbre, etc.) in determining segments. Segments are usually identified as contiguous elements but may be non-contiguous as well. The consistency of a musical surface composed of small groups of pitch-classes is regarded by Forte as a foundation for making statements about large-scale structure. -
On Chords Generating Scales; Three Compositions for Orchestra
INFORMATION TO USERS This reproduction was made from a copy of a document sent to us for microfilming. While the most advanced technology has been used to photograph and reproduce this document, the quality of the reproduction is heavily dependent upon the quality of the material submitted. The following explanation of techniques is provided to help clarify markings or notations which may appear on this reproduction. 1. The sign or “target” for pages apparently lacking from the document photographed is “Missing Page(s)”. If it was possible to obtain the missing page(s) or section, they are spliced into the film along with adjacent pages. This may have necessitated cutting through an image and duplicating adjacent pages to assure complete continuity. 2. When an image on the film is obliterated with a round black mark, it is an indication of either blurred copy because of movement during exposure, duplicate copy, or copyrighted materials that should not have been filmed. For blurred pages, a good image of the page can be found in the adjacent frame. If copyrighted materials were deleted, a target note will appear listing the pages in the adjacent frame. 3. When a map, drawing or chart, etc., is part of the material being photographed, a definite method of “sectioning” the material has been followed. It is customary to begin filming at the upper left hand comer of a large sheet and to continue from left to right in equal sections with small overlaps. If necessary, sectioning is continued again—beginning below the first row and continuing on until complete. -
1 Chapter 1 a Brief History and Critique of Interval/Subset Class Vectors And
1 Chapter 1 A brief history and critique of interval/subset class vectors and similarity functions. 1.1 Basic Definitions There are a few terms, fundamental to musical atonal theory, that are used frequently in this study. For the reader who is not familiar with them, we present a quick primer. Pitch class (pc) is used to denote a pitch name without the octave designation. C4, for example, refers to a pitch in a particular octave; C is more generic, referring to any and/or all Cs in the sonic spectrum. We assume equal temperament and enharmonic equivalence, so the distance between two adjacent pcs is always the same and pc C º pc B . Pcs are also commonly labeled with an integer. In such cases, we will adopt the standard of 0 = C, 1 = C/D, … 9 = A, a = A /B , and b = B (‘a’ and ‘b’ are the duodecimal equivalents of decimal 10 and 11). Interval class (ic) represents the smallest possible pitch interval, counted in number of semitones, between the realization of any two pcs. For example, the interval class of C and G—ic(C, G)—is 5 because in their closest possible spacing, some C and G (C down to G or G up to C) would be separated by 5 semitones. There are only six interval classes (1 through 6) because intervals larger than the tritone (ic6) can be reduced to a smaller number (interval 7 = ic5, interval 8 = ic4, etc.). Chapter 1 2 A pcset is an unordered set of pitch classes that contains at most one of each pc.