Temporal-Scope Grammars for Polyphonic Music Generation

Lukas Eibensteiner, Martin Ilčík, Michael Wimmer
Temporal-Scope Grammars for Polyphonic Music Generation
In Proceedings of the 9th ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design (FARM ’21). August 2021.
[preprint] [demo]

Information

  • Publication Type: Conference Paper
  • Workgroup(s)/Project(s):
  • Date: August 2021
  • Booktitle: Proceedings of the 9th ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design (FARM ’21)
  • Call for Papers: Call for Paper
  • Date (from): 27. August 2021
  • Date (to): 27. August 2021
  • DOI: https://doi.org/10.1145/3471872.3472971
  • Event: ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design
  • ISBN: 978-1-4503-8613-5/21/08
  • Lecturer: Lukas Eibensteiner
  • Location: Virtual
  • Open Access: no
  • Publisher: ACM
  • Keywords: algorithmic composition, music, domain specific language

Abstract

We present temporal-scope grammars for automatic composition of polyphonic music. In the context of this work, polyphony can refer to any arrangement of musical entities (notes, chords, measures, etc.) that is not purely sequential in the time dimension. Given that the natural output of a grammar is a sequence, the generation of sequential structures, such as melodies, harmonic progressions, and rhythmic patterns, follows intuitively. By contrast, we associate each musical entity with an independent temporal scope, allowing the representation of arbitrary note arrangements on every level of the grammar. With overlapping entities we can model chords, drum patterns, and parallel voices – polyphony on small and large scales. We further propose the propagation of sub-grammar results through the derivation tree for synchronizing independently generated voices. For example, we can synchronize the notes of a melody and bass line by reading from a shared harmonic progression.

Additional Files and Images

Additional images and videos

Additional files

Weblinks

BibTeX

@inproceedings{eibens-2021-tsgpmg,
  title =      "Temporal-Scope Grammars for Polyphonic Music Generation",
  author =     "Lukas Eibensteiner and Martin Il\v{c}\'{i}k and Michael
               Wimmer",
  year =       "2021",
  abstract =   "We present temporal-scope grammars for automatic composition
               of polyphonic music. In the context of this work, polyphony
               can refer to any arrangement of musical entities (notes,
               chords, measures, etc.) that is not purely sequential in the
               time dimension. Given that the natural output of a grammar
               is a sequence, the generation of sequential structures, such
               as melodies, harmonic progressions, and rhythmic patterns,
               follows intuitively. By contrast, we associate each musical
               entity with an independent temporal scope, allowing the
               representation of arbitrary note arrangements on every level
               of the grammar. With overlapping entities we can model
               chords, drum patterns, and parallel voices – polyphony on
               small and large scales. We further propose the propagation
               of sub-grammar results through the derivation tree for
               synchronizing independently generated voices. For example,
               we can synchronize the notes of a melody and bass line by
               reading from a shared harmonic progression.",
  month =      aug,
  booktitle =  "Proceedings of the 9th ACM SIGPLAN International Workshop on
               Functional Art, Music, Modelling, and Design (FARM ’21)",
  doi =        "https://doi.org/10.1145/3471872.3472971",
  event =      "ACM SIGPLAN International Workshop on Functional Art, Music,
               Modelling, and Design",
  isbn =       "978-1-4503-8613-5/21/08",
  location =   "Virtual",
  publisher =  "ACM",
  keywords =   "algorithmic composition, music, domain specific language",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2021/eibens-2021-tsgpmg/",
}