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Erschienen in:
2018 | OriginalPaper | Buchkapitel
On the Use of Matrix Based Representation to Deal with Automatic Composer Recognition
verfasst von : Izaro Goienetxea, Iñigo Mendialdua, Basilio Sierra
Erschienen in: AI 2018: Advances in Artificial Intelligence
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Abstract
In this article the use of a matrix based representation of pieces is tested for the classification of musical pieces of some well known classical composers. The pieces in two corpora have been represented in two ways: matrices of interval pair probabilities and a set of 12 global features which had previously been used in a similar task. The classification accuracies of both representations have been computed using several supervised classification algorithms. A class binarization technique has also been applied to study how the accuracies change with this kind of methods. Promising results have been obtained which show that both the matrix representation and the class binarization techniques are suitable to be used in the automatic composer recognition problem.