Automatically calculating tonal tension

Since the early years of the past century, many scholars have focused their efforts towards designing models to better understand the way listeners perceive musical tension. From the existing models, Lerdahl’s has shown strong correlations against tension judgements provided by human listeners and has been used to make accurate predictions of musical tension. However, a full automation of Lerdahl’s model of tension has not yet been made available. This paper presents a computational approach to automatically calculate musical tension according to Lerdahl’s model, with a publicly available implementation

Tension-driven Automatic Music Generation

The Ancient Greeks are one of the first civilisations we know of to have created algorithms to compose music. Since then, algorithmic techniques have vastly improved with increasingly sophisticated computers. In the last two decades, much research in this area has focused on two goals: designing algorithms which generate music as close as possible to that of human composers and implementing those algorithms to automatically generate music in interactive scenarios, such as video games. To meet these goals, automatically generated music should: - focus on higher-level concepts, such as musical tension, - have long-term structure, and - be able to adapt to changes in real time. Combining these three requirements is, however, a challenging task. This dissertation investigates three steps to overcome this challenge. First, we argue that Lerdahl’s model of musical tension is suited to the automatic generation of tonal music that has long-term structure and that matches a given tension profile. By means of an illustrative example, we review Lerdhal’s model and implement a novel computational system to automate it. Second, we show that an effective generation strategy is to combine statistical methods with both rule-based methods and generative grammars to create a music generation system. Third, we implement the system and evaluate it through a collection of computational tests and empirical studies. Our evaluation shows that: (1) the system works effectively in real time, as long as the input tension profiles do not contain too many steep transitions, (2) the hierarchical structure perceived by listeners matches the patterns intended by the system in the generated music, and (3) tension-changing input profiles are accurately matched by the generated music

A Derivation of the Tonal Hierarchy from Basic Perceptual Processes

In recent decades music psychologists have explained the functioning of tonal music in terms of the tonal hierarchy, a stable schema of relative structural importance that helps us interpret the events in a passage of tonal music. This idea has been most influentially disseminated by Carol Krumhansl in her 1990 monograph Cognitive Foundations of Musical Pitch. Krumhansl hypothesized that this sense of the importance or centrality of certain tones of a key is learned through exposure to tonal music, in particular by learning the relative frequency of appearance of the various pitch classes in tonal passages. The correlation of pitch-class quantity and structural status has been the subject of a number of successful studies, leading to the general acceptance of the pitch-distributional account of tonal hierarchy in the field of music psychology. This study argues that the correlation of pitch-class quantity with structural status is a byproduct of other, more fundamental perceptual properties, all of which are derived from aspects of everyday listening. Individual chapters consider the phenomena of consonance and dissonance, intervallic rootedness, the short-term memory for pitch collection, and the interaction of temporal ordering and voice-leading that Jamshed Bharucha calls melodic anchoring. The study concludes with an elaborate self-experiment that observes the interaction of these properties in a pool of 275 stimuli, each of which is constructed from a single dyad plus one subsequent tone

The Butterfly Schema as a Product of the Tendency for Congruence and Hierarchical Selection in the Instrumental Musical Grammar of the Classical Period

Diverging explanations of local multiparametric schemata are found in music of the common practice period (c. 1600–c. 1900). Associative statistical theories describe schemata as situated structures in particular times and places, whereas generative theories present these constructions as features formed through stability in universal and general rule systems. Associative-statistical theories of schemata elucidate the culturally conditioned relationships between features (distinctive attributes commonly used in grammars and schemata), but do not show the influence of universal psychological constraints; generative theories reveal the implicit structure of music, but do not formalise particular grammatical features and contexts. A synthesis of generative and associative-statistical approaches is necessary to model the interaction between universal and particular constraints of grammars and schemata. This dissertation focuses on a novel localised schema formed in the Classical instrumental grammar, termed the butterfly schema. It is posited that the butterfly schema is generated by a tendency for congruence that is manifest in and between the particular features of this grammar. Computational musicology and psychology provide interdisciplinary insight on the formal possibilities and limitations of grammatical structure. Computational models of schemata and grammars show how the congruent features of musical structure can be represented and formalised. However, they also highlight the difficulties found in the automatic analyses of multiparametric relationships, and may be limited on account of their inductive frameworks. Psychological approaches are important for establishing universal laws of cognition, but are limited in their potential to account for the diversity of musical structuring in grammars. The synthesis of associative-statistical and generative approaches in the present dissertation permits modelling the combination of the universal and particular attributes of butterfly schemata. Butterfly schemata are dependent on the particular grammars of periods of history, but are constrained by the tendency for congruence, which is proposed to be a cognitive universal. The features of the butterfly schema and the Classical instrumental grammar are examined and compared against the features of the Baroque and Romantic grammars, showing how they are formed from diverse types of congruent structuring. The butterfly schema is a congruent grammatical category of the Classical instrumental grammar that comprises: chords that are close to the tonic in pitch space (with a chiastic tension curve starting and ending on the tonic); a textural and metrical structure that is regular and forms a regular duple hierarchy at the level of regular functional harmonic change and at two immediately higher levels; and simple harmonic-rhythm ratios (1:1 and 3:1). A survey conducted using arbitrary corpora in European instrumental music, c. 1750–c.1850, shows the distribution of butterfly schemata. Butterfly schemata are more common in the Classical-period sample (c. 1750–c. 1800) than in the Romantic-period sample (c. 1800–c.1850), suggesting that the tendency for congruence manifest in and between the features common in the Classical grammar generates butterfly schemata. A second component to the statistical analysis concerns the type of schemata observed, since the tendency for congruence is presumed to also apply to the type of features that form in butterfly schemata. Maximally congruent features are generated more commonly than minimally congruent features, indicating the influence of the tendency for congruence. This dissertation presents a formulation of the Classical instrumental grammar as a multiparametrically congruent system, and a novel explanation and integration of the concepts of grammars and schemata. A final component to the dissertation poses that the features of the Classical instrumental grammar and butterfly schema follow a distinct order of dependency, governed by the mechanism of selection in culture. Although the tendency for congruence governs all features of a grammar, features are also formed by the top-down action of culture which selects those features. Thus, a top-down hierarchical selection model is presented which describes how the butterfly schema is formed through the order of selection of features in the Classical instrumental grammar

Computational Creativity and Music Generation Systems: An Introduction to the State of the Art

Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers. One of its most prolific subfields is that of Music Generation (also called Algorithmic Composition or Musical Metacreation), that uses computational means to compose music. Due to the multidisciplinary nature of this research field, it is sometimes hard to define precise goals and to keep track of what problems can be considered solved by state-of-the-art systems and what instead needs further developments. With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation. To do so, we first give a picture of the research on the definition and the evaluation of creativity, both human and computational, needed to understand how computational means can be used to obtain creative behaviors and its importance within Artificial Intelligence studies. We then review the state of the art of Music Generation Systems, by citing examples for all the main approaches to music generation, and by listing the open challenges that were identified by previous reviews on the subject. For each of these challenges, we cite works that have proposed solutions, describing what still needs to be done and some possible directions for further research

Computer Mediated Music Production: a Study of Abstraction and Activity

Human Computer Interaction research has a unique challenge in understanding the activity systems of creative professionals, and designing the user-interfaces to support their work. In these activities, the user is involved in the process of building and editing complex digital artefacts through a process of continued refinement, as is seen in computer aided architecture, design, animation, movie-making, 3D modelling, interactive media (such as shockwave-flash), as well as audio and music production. This thesis examines the ways in which abstraction mechanisms present in music production systems interplay with producers' activity through a collective case study of seventeen professional producers. From the basis of detailed observations and interviews we examine common abstractions provided by the ubiquitous multitrack-mixing metaphor and present design implications for future systems

Utilizing Computer Programming to Analyze Post-Tonal Music: A Segmentation and Contour Analysis of Twentieth-Century Music for Solo Flute

Two concepts will be synthesized in this dissertation: 1) the creation of accessible computer applications for melodic segmentation and contour reduction and 2) the application of segmentation and contour reduction to analyze twentieth-century post-tonal works for unaccompanied flute. Two analytical methodologies have been chosen: James Tenney and Larry Polanski\u27s Gestalt segmentation theory and Robert Schultz\u27s refinement of Robert Morris\u27s contour reduction algorithm. The investigation also utilizes Robert Schultz\u27s concept of diachronic-transformational analysis in conjunction with contour reduction. While both segmentation and contour reduction are invaluable analytical tools, they are meticulous and time-consuming processes. Computer implementation of these algorithmic procedures produces quick and accurate results while reducing analyst fatigue and human error. Microsoft Excel is used to complete melodic segmentation. Java programming language is used to create a contour reduction application. Each implementation greatly reduces the time needed to segment and analyze a melody. Computer programming is combined with pitch class set analysis to produce informed and expressive musical interpretations

Computational Models of Expressive Music Performance: A Comprehensive and Critical Review

Expressive performance is an indispensable part of music making. When playing a piece, expert performers shape various parameters (tempo, timing, dynamics, intonation, articulation, etc.) in ways that are not prescribed by the notated score, in this way producing an expressive rendition that brings out dramatic, affective, and emotional qualities that may engage and affect the listeners. Given the central importance of this skill for many kinds of music, expressive performance has become an important research topic for disciplines like musicology, music psychology, etc. This paper focuses on a specific thread of research: work on computational music performance models. Computational models are attempts at codifying hypotheses about expressive performance in terms of mathematical formulas or computer programs, so that they can be evaluated in systematic and quantitative ways. Such models can serve at least two purposes: they permit us to systematically study certain hypotheses regarding performance; and they can be used as tools to generate automated or semi-automated performances, in artistic or educational contexts. The present article presents an up-to-date overview of the state of the art in this domain. We explore recent trends in the field, such as a strong focus on data-driven (machine learning) approaches; a growing interest in interactive expressive systems, such as conductor simulators and automatic accompaniment systems; and an increased interest in exploring cognitively plausible features and models. We provide an in-depth discussion of several important design choices in such computer models, and discuss a crucial (and still largely unsolved) problem that is hindering systematic progress: the question of how to evaluate such models in scientifically and musically meaningful ways. From all this, we finally derive some research directions that should be pursued with priority, in order to advance the field and our understanding of expressive music performance

Topics in Programming Languages, a Philosophical Analysis through the case of Prolog

[EN]Programming languages seldom find proper anchorage in philosophy of logic, language and science. is more, philosophy of language seems to be restricted to natural languages and linguistics, and even philosophy of logic is rarely framed into programming languages topics. The logic programming paradigm and Prolog are, thus, the most adequate paradigm and programming language to work on this subject, combining natural language processing and linguistics, logic programming and constriction methodology on both algorithms and procedures, on an overall philosophizing declarative status. Not only this, but the dimension of the Fifth Generation Computer system related to strong Al wherein Prolog took a major role. and its historical frame in the very crucial dialectic between procedural and declarative paradigms, structuralist and empiricist biases, serves, in exemplar form, to treat straight ahead philosophy of logic, language and science in the contemporaneous age as well. In recounting Prolog's philosophical, mechanical and algorithmic harbingers, the opportunity is open to various routes. We herein shall exemplify some: - the mechanical-computational background explored by Pascal, Leibniz, Boole, Jacquard, Babbage, Konrad Zuse, until reaching to the ACE (Alan Turing) and EDVAC (von Neumann), offering the backbone in computer architecture, and the work of Turing, Church, Gödel, Kleene, von Neumann, Shannon, and others on computability, in parallel lines, throughly studied in detail, permit us to interpret ahead the evolving realm of programming languages. The proper line from lambda-calculus, to the Algol-family, the declarative and procedural split with the C language and Prolog, and the ensuing branching and programming languages explosion and further delimitation, are thereupon inspected as to relate them with the proper syntax, semantics and philosophical élan of logic programming and Prolog

AN APPROACH TO MACHINE DEVELOPMENT OF MUSICAL ONTOGENY

This Thesis pursues three main objectives: (i) to use computational modelling to explore how music is perceived, cognitively processed and created by human beings; (ii) to explore interactive musical systems as a method to model and achieve the transmission of musical influence in artificial worlds and between humans and machines; and (iii) to experiment with artificial and alternative developmental musical routes in order to observe the evolution of musical styles. In order to achieve these objectives, this Thesis introduces a new paradigm for the design of computer interactive musical systems called the Ontomemetical Model of Music Evolution - OMME, which includes the fields of musical ontogenesis and memetlcs. OMME-based systems are designed to artificially explore the evolution of music centred on human perceptive and cognitive faculties. The potential of the OMME is illustrated with two interactive musical systems, the Rhythmic Meme Generator (RGeme) and the Interactive Musical Environments (iMe). which have been tested in a series of laboratory experiments and live performances. The introduction to the OMME is preceded by an extensive and critical overview of the state of the art computer models that explore musical creativity and interactivity, in addition to a systematic exposition of the major issues involved in the design and implementation of these systems. This Thesis also proposes innovative solutions for (i) the representation of musical streams based on perceptive features, (ii) music segmentation, (iii) a memory-based music model, (iv) the measure of distance between musical styles, and (v) an impi*ovisation-based creative model