DogDog: Soma-Based Interface Design for an Improvising Musician

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Abstract

Improvisation is embodied thought and expression. This paper outlines strategies and tactics to design expressive musical interfaces for improvisers. Some of these strategies are explored through a case study: a non-tactile hand-arm movement interface controlling a granular synthesizer (DogDog), based on high-level movement descriptors. The research through design and performance experience indicates that movement quality descriptors are inherently scalable from hand-arm movements to full body interaction, and that a textural approach to motion tracking fits well the morphing sonic masses generated through granular sound synthesis.
Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Movement and Computing, MOCO 2020
Number of pages4
PublisherAssociation for Computing Machinery
Publication date15 Jul 2020
Pages1-4
ISBN (Electronic)9781450375054
DOIs
Publication statusPublished - 15 Jul 2020
Event7th International Conference on Movement and Computing, MOCO 2020 - Jersey City, Virtual, United States
Duration: 15 Jul 202017 Jul 2020

Conference

Conference7th International Conference on Movement and Computing, MOCO 2020
CountryUnited States
CityJersey City, Virtual
Period15/07/202017/07/2020
SponsormBrainTrain
SeriesACM International Conference Proceeding Series

Keywords

  • Embodied Interaction
  • Granular Synthesis
  • Mapping
  • Movement Descriptors
  • Sound

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  • Cite this

    Bigoni, F., & Erkut, C. (2020). DogDog: Soma-Based Interface Design for an Improvising Musician. In Proceedings of the 7th International Conference on Movement and Computing, MOCO 2020 (pp. 1-4). Association for Computing Machinery. ACM International Conference Proceeding Series https://doi.org/10.1145/3401956.3404242