A graph grammar programming style for recognition of music notation

Fahmy, Hoda; Blostein, Dorothea

doi:10.1007/bf01211933

Cited by 47 publications

(26 citation statements)

References 11 publications

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“…The Maggraphens' experience mirrors our own: as we set out to apply graph rewriting to diagram recognition [FaBl93] [GrBl95] [Fahm95], we found it hard to figure out how to organize our computation. A careful reading of the literature was only of limited help: we found extensive discussion of graphrewriting mechanisms, but little discussion of systems issues, and few examples of significantly-large graph-rewriting systems.…”

Section: The Maggraphensmentioning

confidence: 99%

“…For example, PROGRES provides transactions and subdiagrams as encapsulation tools [ZüSc92]. Ordering can be used to structure the computation into phases; for example, Build-Constrain-(Rank)-Incorporate recognition stages are used in [FaBl93] [GrBl95].…”

Section: Modular Control Specificationmentioning

confidence: 99%

“…It is critical that these noise-reduction rules be applied first, and exhaustively, before application of rules for recognition of transistors, capacitors, and so on. Similarly, a recognition approach for music notation [FaBl93] uses ordered recognition stages, each of which consists of three ordered phases (Build creates edges, Weed removes inconsistent edges, and Incorporate prunes the graph while adding semantic information to attributes). Graph applications in software engineering have made extensive use of ordered graph rewriting (e.g.…”

Section: Ordered Graph Rewritingmentioning

confidence: 99%

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Issues in the practical use of graph rewriting

Blostein

Fahmy

Grbavec

1996

Lecture Notes in Computer Science

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Abstract. Graphs are a popular data structure, and graph-manipulation programs are common. Graph manipulations can be cleanly, compactly, and explicitly described using graph-rewriting notation.However, when a software developer is persuaded to try graph rewriting, several problems commonly arise. Primarily, it is difficult for a newcomer to develop a feel for how computations are expressed via graph rewriting. Also, graph-rewriting is not convenient for solving all aspects of a problem: better mechanisms are needed for interfacing graph rewriting with other styles of computation. Efficiency considerations and the limited availability of development tools further limit practical use of graph rewriting. The inaccessible appearance of the graph-rewriting literature is an additional hindrance. These problems can be addressed through a combination of "public relations" work, and further research and development, thereby promoting the widespread use of graph rewriting.

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Section: The Maggraphensmentioning

confidence: 99%

Section: Modular Control Specificationmentioning

confidence: 99%

Section: Ordered Graph Rewritingmentioning

confidence: 99%

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Issues in the practical use of graph rewriting

Blostein

Fahmy

Grbavec

1996

Lecture Notes in Computer Science

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“…Other approaches to OMI have used temporal trees (Diener 1989) or labeled graphrewriting systems (Fahmy and Blostein 1993) as the internal data structure (Section 1.2.2).…”

Section: Glyph Listmentioning

confidence: 99%

“…A number of approaches to OMI use two-dimensional graph grammars as the central problem-solving mechanism (Fahmy and Blostein 1993, Couasnon and Camillerapp 1994, Baumann 1995. Graph grammars parse the relationships between symbols on the page by matching them to a set of syntactic patterns.…”

Section: Introductionmentioning

confidence: 99%

Selected Research in Computer Music

Droettboom¹

2017

Preprint

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This thesis describes three interrelated projects that cut across the author's interests in musical information representation and retrieval, programming language theory, machine learning and human/computer interaction.I. Optical music recognition. This first part introduces an optical music interpretation (OMI) system that derives musical information from the symbols on sheet music.The first chapter is an introduction to OMI's parent field of optical music recognition (OMR), and to the present implementation as created for the Levy project.It is important that OMI has a representation standard in which to create its output. Therefore, the second chapter is a somewhat tangential but necessary study of computer-based musical representation languages, with particular emphasis on GUIDO and Mudela.The third and core chapter describes the processes involved in the present optical music interpretation system. While there are some details related to its implementation in the Python programming language, most of the material involves issues surrounding music notation rather than computer programming.The fourth chapter demonstrates how the logical musical data generated by the OMI system can be used as part of a musical search engine.II. Tempo extraction. The second part presents a system to automatically obtain the tempo and rubato curves from recorded performances, by aligning them to strict-tempo MIDI renderings of the same piece of music. The usefulness of such a system in the context of current musicological research is explored.III. Realtime digital signal processing programming environment. Lastly, a portable and flexible system for realtime digital signal processing (DSP) is presented. This system is both easyto-use and powerful, in large part because it takes advantage of existing mature technologies. This framework provides the foundation for easier experimentation in new directions in audio and video processing, including physical modeling and motion tracking.iii

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Computing with graphs and graph transformations

Blostein

Schürr

1999

Softw: Pract. Exper.

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Many software applications require the construction and manipulation of graphs. In standard programming languages, this is accomplished using low-level mechanisms such as pointer manipulation or array indexing. In contrast, graph productions are a convenient high-level visual notation for coding graph modifications. A graph production replaces one subgraph by another subgraph. Graph productions can define a graph grammar and graph language, or can directly transform an input graph into an output graph. Graph transformation has been applied in many areas, including the definition of visual languages and their tools, the construction of software development environments, the definition of constraint programming algorithms, the modeling of distributed systems, and the construction of neural networks. One application is presented in detail: the interpretation of mathematical notation in scanned document images. The graph models the set of mathematical symbols, and their spatial and logical relationships. This graph is transformed by productions written in the PROGRES language.

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A graph grammar programming style for recognition of music notation

Cited by 47 publications

References 11 publications

Issues in the practical use of graph rewriting

Issues in the practical use of graph rewriting

Selected Research in Computer Music

Computing with graphs and graph transformations

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