183,498 research outputs found

    Automatic Music Composition using Answer Set Programming

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    Music composition used to be a pen and paper activity. These these days music is often composed with the aid of computer software, even to the point where the computer compose parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named ANTON, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes ANTON unique in the growing area of algorithmic composition. With near real-time composition, ANTON reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, ANTON provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems. This paper has been accepted for publication in Theory and Practice of Logic Programming (TPLP).Comment: 31 pages, 10 figures. Extended version of our ICLP2008 paper. Formatted following TPLP guideline

    Integrating Segmentation and Similarity in Melodic Analysis

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    The recognition of melodic structure depends on both the segmentation into structural units, the melodic motifs, and relations of motifs which are mainly determined by similarity. Existing models and studies of segmentation and motivic similarity cover only certain aspects and do not provide a comprehensive or coherent theory. In this paper an Integrated Segmentation and Similarity Model (ISSM) for melodic analysis is introduced. The ISSM yields an interpretation similar to a paradigmatic analysis for a given melody. An interpretation comprises a segmentation, assignments of related motifs and notes, and detailed information on the differences of assigned motifs and notes. The ISSM is based on generating and rating interpretations to find the most adequate one. For this rating a neuro-fuzzy-system is used, which combines knowledge with learning from data. The ISSM is an extension of a system for rhythm analysis. This paper covers the model structure and the features relevant for melodic and motivic analysis. Melodic segmentation and similarity ratings are described and results of a small experiment which show that the ISSM can learn structural interpretations from data and that integrating similarity improves segmentation performance of the model

    Interactive Spaces. Models and Algorithms for Reality-based Music Applications

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    Reality-based interfaces have the property of linking the user's physical space with the computer digital content, bringing in intuition, plasticity and expressiveness. Moreover, applications designed upon motion and gesture tracking technologies involve a lot of psychological features, like space cognition and implicit knowledge. All these elements are the background of three presented music applications, employing the characteristics of three different interactive spaces: a user centered three dimensional space, a floor bi-dimensional camera space, and a small sensor centered three dimensional space. The basic idea is to deploy the application's spatial properties in order to convey some musical knowledge, allowing the users to act inside the designed space and to learn through it in an enactive way

    The transmission of style in Scottish fiddling

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    A Semantic Approach To Autonomous Mixing

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    Software agents in music and sound art research/creative work: Current state and a possible direction

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    Composers, musicians and computer scientists have begun to use software-based agents to create music and sound art in both linear and non-linear (non-predetermined form and/or content) idioms, with some robust approaches now drawing on various disciplines. This paper surveys recent work: agent technology is first introduced, a theoretical framework for its use in creating music/sound art works put forward, and an overview of common approaches then given. Identifying areas of neglect in recent research, a possible direction for further work is then briefly explored. Finally, a vision for a new hybrid model that integrates non-linear, generative, conversational and affective perspectives on interactivity is proposed

    Designing constraints: composing and performing with digital musical systems

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    This paper investigates two central terms in Human Computer Interaction (HCI) – affordances and constraints – and studies their relevance to the design and understanding of digital musical systems. It argues that in the analysis of complex systems, such as new interfaces for musical expression (NIME), constraints are a more productive analytical tool than the common HCI usage of affordances. Constraints are seen as limitations enabling the musician to encapsulate a specific search space of both physical and compositional gestures, proscribing complexity in favor of a relatively simple set of rules that engender creativity. By exploring the design of three different digital musical systems, the paper defines constraints as a core attribute of mapping, whether in instruments or compositional systems. The paper describes the aspiration for designing constraints as twofold: to save time, as musical performance is typically a real-time process, and to minimize the performer’s cognitive load. Finally, it discusses skill and virtuosity in the realm of new musical interfaces for musical expression with regard to constraints
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