Computing in musicology, 1966–91

While there are many parallels between computing activities in musicology and those in other humanities disciplines, the particular nature of musical material and the ways in which this must be accommodated set many activities apart from those in text-based disciplines. As in other disciplines, early applications were beset by hardware constraints, which placed a premium on expertise and promoted design-intensive projects. Massive musical encoding and bibliographical projects were initiated. Diversification of hardware platforms and languages in the Seventies led to task-specific undertakings, including preliminary work on many of today's programs for music printing and analysis. The rise of personal computers and associated general-purpose software in the Eighties has enabled many scholars to pursue projects individually, particularly with the assistance of database, word processing, and notation software. Current issues facing the field include the need for standards for data interchange, the creation of banks of reusable data, the establishment of qualitative standards for encoded data, and the encouragement of realistic appraisals of what computers can do. The musicologist Eleanor Selfridge-Field, who is the author of three books on Italian music and numerous articles, editions, and reviews, has worked at CCARH since its founding in 1984. Her most recent book, The Music of Benedetto and Alessandro Marcello (Oxford: Clarendon Press, 1990), which contains 1300 musical examples, was produced from camera-ready copy supplied by CCARH. Drs. Hewlett and Selfridge-Field jointly edit the series Computing in Musicology, which is published by CCARH, and co-chair the International Musicological Society's Study Group on Musical Data and Computer Applications.     

Computational ludics

We reformulate the theory of ludics introduced by J.-Y. Girard from a computational point of view. We introduce a handy term syntax for designs, the main objects of ludics. Our syntax also incorporates explicit cuts for attaining computational expressivity. In addition, we consider design generators that allow for finite representation of some infinite designs. A normalization procedure in the style of Krivine’s abstract machine directly works on generators, giving rise to an effective means of computation over infinite designs.The acceptance relation between machines and words, a basic concept in computability theory, is well expressed in ludics by the orthogonality relation between designs. Fundamental properties of ludics are then discussed in this concrete context. We prove three characterization results that clarify the computational powers of three classes of designs. (i) Arbitrary designs may capture arbitrary sets of finite data. (ii) When restricted to finitely generated ones, designs exactly capture the recursively enumerable languages. (iii) When further restricted to cut-free ones as in Girard’s original definition, designs exactly capture the regular languages.We finally describe a way of defining data sets by means of logical connectives, where the internal completeness theorem plays an essential role.     

Computational humor

In an effort to focus on tractable problems, computational natural language understanding systems have typically addressed language phenomena that are amenable to combinatorial approaches using static and stereotypical semantic representations. Although such approaches are adequate for much of language, they're not easily extended to capture humans' more creative language interpretation capacities. This paper proposes a model of humor comprehension based on frame-shifting within a simulation-based natural-language-understanding system.     

Computational Aesthetics

Guest Editors Bruce Gooch and Brian Wyvill discuss computational aesthetics and the articles that comprise their special issue.     

Computational Meta-Ethics

It has been argued that ethically correct robots should be able to reason about right and wrong. In order to do so, they must have a set of do’s and don’ts at their disposal. However, such a list may be inconsistent, incomplete or otherwise unsatisfactory, depending on the reasoning principles that one employs. For this reason, it might be desirable if robots were to some extent able to reason about their own reasoning—in other words, if they had some meta-ethical capacities. In this paper, we sketch how one might go about designing robots that have such capacities. We show that the field of computational meta-ethics can profit from the same tools as have been used in computational metaphysics.     

Computational programming technologies

Problems arising in computational programming in connection with the approaching transition to using exaflop hardware are discussed. The discussion is focused on the lifecycle of mathematical modeling and related general problems that are being solved in the course of model development. This area is (and is going to be forever) one of the main consumers of computational resources. The study of its methods and approaches makes it possible to formulate basic directions of assumed progress caused by necessity of formation of computational programming technologies.     

Computational Plenoptic Imaging

The plenoptic function is a ray‐based model for light that includes the colour spectrum as well as spatial, temporal and directional variation. Although digital light sensors have greatly evolved in the last years, one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly lost, except for a two‐dimensional, spatially varying subset—the common photograph. In this state‐of‐the‐art report, we review approaches that optically encode the dimensions of the plenoptic function transcending those captured by traditional photography and reconstruct the recorded information computationally.     

Computational Cultural Dynamics

Computational cultural dynamics blends the behavioral and social sciences - fields such as political science, psychology, journalism, anthropology, and sociology - with technological fields such as computer science, computational linguistics, game theory, statistical modeling, and operations research.