Eric J. Isaacson

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Though music is fundamentally an aural phenomenon, we often communicate about music through visual means. The paper examines a number of visualization techniques developed for music, focusing especially on those developed for music analysis by specialists in the field, but also looking at some less successful approaches. It is hoped that, by presenting them(More)
“Academic musicians,” students and faculty in schools of music, have music IR needs that differ from those of the mass-market consumer. This paper describes the characteristics of this user group, the types of musical information they use and how they use them, and the kinds of IR tasks they need to perform. A section describes the special needs of the(More)
Neural networks are used to study two issues pertaining to atonal music. In the first part of the paper, feed-forward neural networks, using a variant of the backpropagation learning algorithm, try to learn a variety of abstract theoretical constructs from pitch-class set theory. First, learning the properties of individual sets is studied. Then a network's(More)