6,095 research outputs found

    Regular expressions as violin bowing patterns

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    String players spend a significant amount of practice time creating and learning bowings. These may be indicated in the music using up-bow and down-bow symbols, but those traditional notations do not capture the complex bowing patterns that are latent within the music. Regular expressions, a mathematical notation for a simple class of formal languages, can describe precisely the bowing patterns that commonly arise in string music. A software tool based on regular expressions enables performers to search for passages that can be handled with similar bowings, and to edit them consistently. A computer-based music editor incorporating bowing patterns has been implemented, using Lilypond to typeset the music. Our approach has been evaluated by using the editor to study ten movements from six violin sonatas by W. A. Mozart. Our experience shows that the editor is successful at finding passages and inserting bowings; that relatively complex patterns occur a number of times; and that the bowings can be inserted automatically and consistently

    A survey of computer uses in music

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    This thesis covers research into the mathematical basis inherent in music including review of projects related to optical character recognition (OCR) of musical symbols. Research was done about fractals creating new pieces by assigning pitches to numbers. Existing musical pieces can be taken apart and reassembled creating new ideas for composers. Musical notation understanding is covered and its requirement for the recognition of a music sheet by the computer for editing and reproduction purposes is explained. The first phase of a musical OCR was created in this thesis with the recognition of staff lines on a good quality image. Modifications will need to be made to take care of noise and tilted images that may result from scanning

    Applying static code analysis for domain-specific languages

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    The use of code quality control platforms for analysing source code is increasingly gaining attention in the developer community. These platforms are prepared to parse and check source code written in a variety of general-purpose programming languages. The emergence of domain-specific languages enables professionals from different areas to develop and describe problem solutions in their disciplines. Thus, source code quality analysis methods and tools can also be applied to software artefacts developed with a domain-specific language. To evaluate the quality of domain-specific language code, every software component required by the quality platform to parse and query the source code must be developed. This becomes a time-consuming and error-prone task, for which this paper describes a model-driven interoperability strategy that bridges the gap between the grammar formats of source code quality parsers and domain-specific text languages. This approach has been tested on the most widespread platforms for designing text-based languages and source code analysis. This interoperability approach has been evaluated on a number of specific contexts in different domain areas

    Analysing symbolic music with probabilistic grammars

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    Recent developments in computational linguistics offer ways to approach the analysis of musical structure by inducing probabilistic models (in the form of grammars) over a corpus of music. These can produce idiomatic sentences from a probabilistic model of the musical language and thus offer explanations of the musical structures they model. This chapter surveys historical and current work in musical analysis using grammars, based on computational linguistic approaches. We outline the theory of probabilistic grammars and illustrate their implementation in Prolog using PRISM. Our experiments on learning the probabilities for simple grammars from pitch sequences in two kinds of symbolic musical corpora are summarized. The results support our claim that probabilistic grammars are a promising framework for computational music analysis, but also indicate that further work is required to establish their superiority over Markov models

    Understanding Optical Music Recognition

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    For over 50 years, researchers have been trying to teach computers to read music notation, referred to as Optical Music Recognition (OMR). However, this field is still difficult to access for new researchers, especially those without a significant musical background: Few introductory materials are available, and, furthermore, the field has struggled with defining itself and building a shared terminology. In this work, we address these shortcomings by (1) providing a robust definition of OMR and its relationship to related fields, (2) analyzing how OMR inverts the music encoding process to recover the musical notation and the musical semantics from documents, and (3) proposing a taxonomy of OMR, with most notably a novel taxonomy of applications. Additionally, we discuss how deep learning affects modern OMR research, as opposed to the traditional pipeline. Based on this work, the reader should be able to attain a basic understanding of OMR: its objectives, its inherent structure, its relationship to other fields, the state of the art, and the research opportunities it affords

    Music analysis and the computer: developing a computer operating system to analyse music, using Johann Sebastian Bach's "well tempered clavier" book 51 to test the methodology

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    "Most computerised and computer-aided musicological projects are written to achieve specific goals. Once achieved or not achieved as the case may be, the projects and their tools are frequently discarded because their dependency upon specific computer hardware and software prevents them from being utilised by other researchers for other projects. What is needed is a system that, using small tools to accomplish small tasks, can be expanded and customized to suit specific needs. This thesis proposes the creation of a music-analysis computer operating system that contains simple commands to perform simple musicological tasks such as the removal of repeated notes from a score or the audible rendition of a melodic line. The tools can be bolted together to form larger tools that perform larger tasks. New tools can be created and added to the operating system with relative ease, and these in turn can be bolted onto old tools. The thesis suggests a basic set of tools derived from old and new analytical methods, proposes a standard for their implementation based on the UNIX computer operating system, and discusses the benefits of using the system and its tools in an analysis of the twenty-four fugues of Johann Sebastian Bach from the "Well Tempered Clavier", Book II.
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