Comb-bound, soft cover - 258 pages, Reprint. PhD thesis, Department of Computer Science, Indiana University, August 1984.
A fascinating work containing a thorough analysis of music notation, a unique set of music examples illustrating its
extremes and a description of the inner workings of the author's music notation program,
which led to the commercial product Nightingale.
From the Abstract...
Producing CMN (conventional music notation) output is most generally viewed as having three aspects: selecting
the symbols to print, positioning them, i.e., deciding where to print them, and actually printing
them. The positioning aspect is the core of the problem: it is essentially a question of formatting, analogous to
formatting natural language text, but much more difficult. A solution to this aspect of the musicians' problem,
that of automatic music formatting, would not only be very valuable to musicians, but would also be quite interesting
and nontrivial from the computer scientist's viewpoint.
I argue, and give examples by major composers to show, that "fully automatic high-quality music notation" is not
merely nontrivial but in general impossible without human-level intelligence. Since current work in artificial
intelligence is far from this level, one must compromise, and three ways are possible: compromise in degree of
automation, in quality of output, or in generality of input. Most workers on the problem have primarily sacrificed
automation. The present work, in contrast, primarily sacrifices generality of input, partly due to historical
accident but partly on philosophical grounds. A major chapter of the dissertation documents my program as so far
implemented. The dissertation concludes with a discussion of the central unsolved problem of automatic music
formatting.
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