The study presents a taxonomy of periodic musical progressions inspired by the properties of Shepard tones, designed for training machine learning models. It is a system, implemented in new computer software, for the synthesis and analysis of music harmony, rhythm, and dynamics in an algorithmic context. In the introduction, motivation is explained for the creation of a new music taxonomy designed for future use with machine learning. In the main part of the text, a new music notation is introduced that enables the representation of any progression of harmony, rhythm, and dynamics in a form of multidimensional arrays. Furthermore, a new taxonomy of Shepard-tone-inspired "Periodic Musical Elements" is introduced and a new method for analysis of musical material is presented together with examples. The paper discusses the benefits of using this method in the perspective of further research connected to algorithmic music composition with machine learning.
In the last few years museums and art galleries, as well as a growing number of artists embraced Non-Fungible Tokens (NFTs) as a new digital mode of exposing, producing, and distributing art. Based upon digitised assets, NFTs are embedded in blockchains: decentralised networks of information exchange on which different kinds of data can be stored without a centralised controlling entity. While commonly associated with cryptocurrencies and financial ledgers of transactions, blockchain technology can support many other types of data (including visual, audio, and video files). For the arts, blockchain might bring radical changes to the ways in which art is generated, communicated, disseminated, and transacted. Despite its vertiginous expansion, the blockchain revolution is happening under the radar of many people and institutions.
With this seminar, the research group MetamusicX (at Orpheus Institute) launched research on NFTs in relation to artistic research. The seminar aimed at mapping the field, exploring the potential of blockchain for music creation, and launching the basis for a blockchain network at the service of artistic research.