939 resultados para Computational music theory
Resumo:
This paper critiques a traditional approach to music theory pedagogy. It argues that music theory courses should draw on pedagogies that reflect the diversity and pluralism inherent in 21st century music making. It presents the findings of an action research project investigating the experiences of undergraduate students undertaking an innovative contemporary art music theory course. It describes the students’ struggle in coming to terms with a course that integrated composing, performing, listening and analysing coupled with what for many was their first exposure to the diversity of contemporary art music. The paper concludes with suggesting that the approach could be adopted more widely throughout music programs.
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We say that a polygon inscribed in the circle is asymmetric if it contains no two antipodal points being the endpoints of a diameter. Given n diameters of a circle and a positive integer k < n, this paper addresses the problem of computing a maximum area asymmetric k-gon having as vertices k < n endpoints of the given diameters. The study of this type of polygons is motivated by ethnomusiciological applications.
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When communicating emotion in music, composers and performers encode their expressive intentions through the control of basic musical features such as: pitch, loudness, timbre, mode, and articulation. The extent to which emotion can be controlled through the systematic manipulation of these features has not been fully examined. In this paper we present CMERS, a Computational Music Emotion Rule System for the control of perceived musical emotion that modifies features at the levels of score and performance in real-time. CMERS performance was evaluated in two rounds of perceptual testing. In experiment I, 20 participants continuously rated the perceived emotion of 15 music samples generated by CMERS. Three music works, each with five emotional variations were used (normal, happy, sad, angry, and tender). The intended emotion by CMERS was correctly identified 78% of the time, with significant shifts in valence and arousal also recorded, regardless of the works’ original emotion.
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This thesis explores melodic and harmonic features of heavy metal, and while doing so, explores various methods of music analysis; their applicability and limitations regarding the study of heavy metal music. The study is built on three general hypotheses according to which 1) acoustic characteristics play a significant role for chord constructing in heavy metal, 2) heavy metal has strong ties and similarities with other Western musical styles, and 3) theories and analytical methods of Western art music may be applied to heavy metal. It seems evident that in heavy metal some chord structures appear far more frequently than others. It is suggested here that the fundamental reason for this is the use of guitar distortion effect. Subsequently, theories as to how and under what principles heavy metal is constructed need to be put under discussion; analytical models regarding the classification of consonance and dissonance and chord categorization are here revised to meet the common practices of this music. It is evident that heavy metal is not an isolated style of music; it is seen here as a cultural fusion of various musical styles. Moreover, it is suggested that the theoretical background to the construction of Western music and its analysis can offer invaluable insights to heavy metal. However, the analytical methods need to be reformed to some extent to meet the characteristics of the music. This reformation includes an accommodation of linear and functional theories that has been found rather rarely in music theory and musicology.
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This paper proposes a new method for local key and chord estimation from audio signals. This method relies primarily on principles from music theory, and does not require any training on a corpus of labelled audio files. A harmonic content of the musical piece is first extracted by computing a set of chroma vectors. A set of chord/key pairs is selected for every frame by correlation with fixed chord and key templates. An acyclic harmonic graph is constructed with these pairs as vertices, using a musical distance to weigh its edges. Finally, the sequences of chords and keys are obtained by finding the best path in the graph using dynamic programming. The proposed method allows a mutual chord and key estimation. It is evaluated on a corpus composed of Beatles songs for both the local key estimation and chord recognition tasks, as well as a larger corpus composed of songs taken from the Billboard dataset.
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The primary goal of this report is to demonstrate how considerations from computational complexity theory can inform grammatical theorizing. To this end, generalized phrase structure grammar (GPSG) linguistic theory is revised so that its power more closely matches the limited ability of an ideal speaker--hearer: GPSG Recognition is EXP-POLY time hard, while Revised GPSG Recognition is NP-complete. A second goal is to provide a theoretical framework within which to better understand the wide range of existing GPSG models, embodied in formal definitions as well as in implemented computer programs. A grammar for English and an informal explanation of the GPSG/RGPSG syntactic features are included in appendices.
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Television’s long-form storytelling has the potential to allow the rippling of music across episodes and seasons in interesting ways. In the integration of narrative, music and meaning found in The O.C. (Fox, FOX 2003-7), popular song’s allusive and referential qualities are drawn upon to particularly televisual ends. At times embracing its ‘disruptive’ presence, at others suturing popular music into narrative, at times doing both at once. With television studies largely lacking theories of music, this chapter draws on film music theory and close textual analysis to analyse some of the programme's music moments in detail. In particular it considers the series-spanning use of Jeff Buckley’s cover of ‘Hallelujah’ (and its subsequent oppressive presence across multiple televisual texts), the end of episode musical montage and the use of recurring song fragments as theme within single episodes. In doing so it highlights music's role in the fragmentation and flow of the television aesthetic and popular song’s structural presence in television narrative. Illustrating the multiplicity of popular song’s use in television, these moments demonstrate song’s ability to provide narrative commentary, yet also make particular use of what Ian Garwood describes as the ability of ‘a non-diegetic song to exceed the emotional range displayed by diegetic characters’ (2003:115), to ‘speak’ for characters or to their feelings, contributing to both teen TV’s melodramatic affect and narrative expression.
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The diagrammatic strong-coupling perturbation theory (SCPT) for correlated electron systems is developed for intersite Coulomb interaction and for a nonorthogonal basis set. The construction is based on iterations of exact closed equations for many - electron Green functions (GFs) for Hubbard operators in terms of functional derivatives with respect to external sources. The graphs, which do not contain the contributions from the fluctuations of the local population numbers of the ion states, play a special role: a one-to-one correspondence is found between the subset of such graphs for the many - electron GFs and the complete set of Feynman graphs of weak-coupling perturbation theory (WCPT) for single-electron GFs. This fact is used for formulation of the approximation of renormalized Fermions (ARF) in which the many-electron quasi-particles behave analogously to normal Fermions. Then, by analyzing: (a) Sham's equation, which connects the self-energy and the exchange- correlation potential in density functional theory (DFT); and (b) the Galitskii and Migdal expressions for the total energy, written within WCPT and within ARF SCPT, a way we suggest a method to improve the description of the systems with correlated electrons within the local density approximation (LDA) to DFT. The formulation, in terms of renormalized Fermions LIDA (RF LDA), is obtained by introducing the spectral weights of the many electron GFs into the definitions of the charge density, the overlap matrices, effective mixing and hopping matrix elements, into existing electronic structure codes, whereas the weights themselves have to be found from an additional set of equations. Compared with LDA+U and self-interaction correction (SIC) methods, RF LDA has the advantage of taking into account the transfer of spectral weights, and, when formulated in terms of GFs, also allows for consideration of excitations and nonzero temperature. Going beyond the ARF SCPT, as well as RF LIDA, and taking into account the fluctuations of ion population numbers would require writing completely new codes for ab initio calculations. The application of RF LDA for ab initio band structure calculations for rare earth metals is presented in part 11 of this study (this issue). (c) 2005 Wiley Periodicals, Inc.
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We have previously shown that a division of the f-shell into two subsystems gives a better understanding of the cohesive properties as well the general behavior of lanthanide systems. In this article, we present numerical computations, using the suggested method. We show that the picture is consistent with most experimental data, e.g., the equilibrium volume and electronic structure in general. Compared with standard energy band calculations and calculations based on the self-interaction correction and LIDA + U, the f-(non-f)-mixing interaction is decreased by spectral weights of the many-body states of the f-ion. (c) 2005 Wiley Periodicals, Inc.
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This thesis is an attempt to unite two distinct and dissimilar musical genres, the music of the Colombian Andes and modem jazz. The compositions to be analyzed in this thesis are meant to function as parts of a whole. Thus, they will be linked by thematic and rhythmic material. In their entirety the pieces will form a suite of dances not unlike those of Baroque composers, with titles that denote the name of the particular air being employed by the composer, who is also the author of this thesis. These individual dances are orchestrated for a jazz ensemble consisting of piano, string bass, drums, alto saxophone, and guitar. The rhythmic underpinning of this work is inspired by the folk music of Colombia and the harmonic content will be derived from the jazz idiom. The purpose of this thesis is to demonstrate the possible product of the fusion of musical disciplines that are on the surface in no way related. This thesis will also attempt to show an example of how cultures can meld socio-artistically.
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The SoundCipher software library provides an easy way to create music in the Processing development environment. With the SoundCipher library added to Processing you can write software programs that make music to go along with your graphics and you can add sounds to enhance your Processing animations or games. SoundCipher provides an easy interface for playing 'notes' on the JavaSound synthesizer, for playback of audio files, and comunicating via MIDI. It provides accurate scheduling and allows events to be organised in musical time; using beats and tempo. It uses a 'score' metaphor that allows the construction of simple or complex musical arrangements. SoundCipher is designed to facilitate the basics of algorithmic music and interactive sound design as well as providing a platform for sophisticated computational music, it allows integration with the Minim library when more sophisticated audio and synthesis functionality is required and integration with the oscP5 library for communicating via open sound control.
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This paper discusses a method, Generation in Context, for interrogating theories of music analysis and music perception. Given an analytic theory, the method consists of creating a generative process that implements the theory in reverse. Instead of using the theory to create analyses from scores, the theory is used to generate scores from analyses. Subjective evaluation of the quality of the musical output provides a mechanism for testing the theory in a contextually robust fashion. The method is exploratory, meaning that in addition to testing extant theories it provides a general mechanism for generating new theoretical insights. We outline our initial explorations in the use of generative processes for music research, and we discuss how generative processes provide evidence as to the veracity of theories about how music is experienced, with insights into how these theories may be improved and, concurrently, provide new techniques for music creation. We conclude that Generation in Context will help reveal new perspectives on our understanding of music.
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The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. This paper shows that an effective version of Shinohara’s notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. Let Omega be a notation for the first limit ordinal. Then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m >0, the class of languages defined by formal systems of length <= m: • is identifiable in the limit from positive data with a mind change bound of Omega (power)m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of Omega × m. The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded Prolog programs, including Shapiro’s linear programs, Arimura and Shinohara’s depth-bounded linearly covering programs, and Krishna Rao’s depth-bounded linearly moded programs. It is also noted that the bound for learning from positive data is tight for the example classes considered.
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Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.