A Viewpoint Approach to Symbolic Music Transformation

Bigo, Louis; Conklin, Darrell

doi:10.1007/978-3-319-46282-0_13

Cited by 4 publications

(4 citation statements)

References 10 publications

(17 reference statements)

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“…In the last step new created harmonic development in dictionary h3 is combined with dictionary r2 of rhythm of the second MIDI file resulting in a new musical composition with regularity/consistency and development. This is the principal advantage of applying a transformational compositional method, where the source composition is taken as a seed and a new composition is obtained by transforming its features [26]. The following descriptions cover the proposed approach in further detail.…”

Section: Preliminary Considerationsmentioning

confidence: 99%

Algorithmic music generation by harmony recombination with genetic algorithm

López-Rincón

Starostenko

Lopez-Rincon

2022

IFS

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Algorithmic music composition has recently become an area of prestigious research in projects such as Google’s Magenta, Aiva, and Sony’s CSL Lab aiming to increase the composers’ tools for creativity. There are advances in systems for music feature extraction and generation of harmonies with short-time and long-time patterns of music style, genre, and motif. However, there are still challenges in the creation of poly-instrumental and polyphonic music, pieces become repetitive and sometimes these systems copy the original files. The main contribution of this paper is related to the improvement of generating new non-plagiary harmonic developments constructed from the symbolic abstraction from MIDI music non-labeled data with controlled selection of rhythmic features based on evolutionary techniques. Particularly, a novel approach for generating new music compositions by replacing existing harmony descriptors in a MIDI file with new harmonic features from another MIDI file selected by a genetic algorithm. This allows combining newly created harmony with a rhythm of another composition guaranteeing the adjustment of a new music piece to a distinctive genre with regularity and consistency. The performance of the proposed approach has been assessed using artificial intelligent computational tests, which assure goodness of the extracted features and shows its quality and competitiveness.

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Section: Preliminary Considerationsmentioning

confidence: 99%

Algorithmic music generation by harmony recombination with genetic algorithm

López-Rincón

Starostenko

Lopez-Rincon

2022

IFS

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“…A system for reharmonizing uplifting trance music based on a newly generated chord sequence was developed by [Bigo and Conklin 2015]. The system was extensively tested in an empirical study, in which Agres et al [2016] found that repetitiveness in harmonic structure and tension, not solely rhythmic structure, is a contributor to listener enjoyment in this form of electronic dance music.…”

Section: General Harmonizationmentioning

confidence: 99%

A Functional Taxonomy of Music Generation Systems

2017

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Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical tasks targeted by different machines and the degree to which they succeed remain open questions. We present a functional taxonomy for music generation systems with reference to existing systems. The taxonomy organizes systems according to the purposes for which they were designed. It also reveals the inter-relatedness amongst the systems. This design-centered approach contrasts with predominant methods-based surveys, and facilitates the identification of grand challenges so as to set the stage for new breakthroughs.

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“…Through the use of start and end markers within the music segments some authors support music navigation, editing and synchronization [21][22][23][24]. Others develop applications for computer-assisted composition and improvisation [25][26][27][28]. In [29] authors study patterns and metrics characterizing musical aspects such as pitch, timbre, and loudness in a specific musical corpus.…”

Section: Related Workmentioning

confidence: 99%

A Proposal for Supporting Learning Flute at Primary School

Bravo¹,

Gónzalez

Cid³

2018

UCAmI 2018

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Music Education is a part of the Primary School curriculum in Spain. Students get only 45 min per week organized by group lessons. Thus, it is complicated for teachers to give individualized attention. Additionally, learning to play an instrument is difficult with the current method. In this paper, we propose a methodology and the development of a digital tool as a complement to learn flute at home, in a persuasive and guided manner, using the virtual teacher metaphor. Students can listen to the selected repertoire, recording their performances and receiving advices from their devices (smartphone or tablet). Finally, the teacher will receive feedback for the evolution of each student in order to offer individual advice in the classroom.

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A Viewpoint Approach to Symbolic Music Transformation

Cited by 4 publications

References 10 publications

Algorithmic music generation by harmony recombination with genetic algorithm

Algorithmic music generation by harmony recombination with genetic algorithm

A Functional Taxonomy of Music Generation Systems

A Proposal for Supporting Learning Flute at Primary School

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