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The analysis we can do includes the following.
- Analysis by note length distribution.
- Analysis by note pitch distribution (relative
to the current key).
- Analysis by the distribution of the intervals
between successive notes.
- Analysis by the distribution of successive
pairs of intervals between notes.
Results from the above analyses can then
be combined with standard cluster analysis techniques or multi-dimensional
scaling to determine the ethnic similarities between tunes in our
We also have programs to generate the type of chord harmonies used in
the database of British folk music. Alternative
harmonies are optimised using a combination of abstract theoretical techniques
(e.g. matching the harmonics of the notes in a phrase, with appropriate
weighting functions, to those of the notes in each possible chord) combined
with heuristics (e.g. the acceptability of certain chords w.r.t the present
key, or the acceptability of certain resolutions). Techniques such as
critical path analysis are used in the final optimisation. (See The Harmonisation
of Melodies by Computer, Eric Foxley, Proc Second Symposium International
Informatique et Musicologie, 1982, Paris).
The harmonies produced can be used in various
- As a basis for harmonies to be used when
playing the music. New non-standard harmonies often appear, which are
- As the basis of further clustering, to
determine which tunes are possible derivatives of others.
- As the basis for awarding marks for given
harmonies. This is the basis of an experimental music harmony course
being built in the Ceilidh or CourseMarker system at the University of Nottingham Computer Science Department.