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2022 | OriginalPaper | Chapter

PAUL: An Algorithmic Composer for Classical Piano Music Supporting Multiple Complexity Levels

Authors : Felix Schön, Hans Tompits

Published in: Progress in Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

Algorithmic composition (AC) refers to the process of creating music by means of algorithms, either for realising music entirely composed by a computer or with the help of a computer. In this paper, we report on the development of the system \(\textsf{PAUL}\), an algorithmic composer for the automatic creation of short pieces of classical piano music, based on a neural-network architecture. The distinguishing feature of \(\textsf{PAUL}\) is that it allows to specify the desired complexity of the output piece in terms of an input parameter, which is a central aspect towards the designated future usage of \(\textsf{PAUL}\) as being part of a tutoring system teaching piano students how to sight-read music. \(\textsf{PAUL}\) employs a long short-term memory (LSTM) neural network to produce the lead track and a sequence-to-sequence neural network for the realisation of the accompanying track. Although \(\textsf{PAUL}\) is still work-in-progress, the obtained results are of reasonable to good quality. In a small-scale study, evaluating the specified vs. the perceived complexity of different pieces generated by \(\textsf{PAUL}\), a clear correlation is observable.

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Title: PAUL: An Algorithmic Composer for Classical Piano Music Supporting Multiple Complexity Levels
Authors: Felix Schön
Hans Tompits
Publisher: Springer International Publishing
Book: Progress in Artificial Intelligence
Print ISBN: 978-3-031-16473-6

Electronic ISBN: 978-3-031-16474-3

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-3-031-16474-3_34

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