A Multimodal Methodology for Music Field Recording and Archival

Juan Sierra, Safeya Alblooshi, Beth Russell, Carlos Guedes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a methodology and production workflow for the field recording of traditional music from the Arabian Gulf. The fact that this music is often performed by groups that are constantly moving in space requires that special strategies are put in place to capture the music while the performers are moving. We developed an approach that makes use of several recorders and microphones (including Ambisonic microphones) synchronized via timecode with video cameras (including 360 cameras) in order to capture the these performances. The goal for developing this methodology is to create high-quality, multi-modal digital collections of this music that can serve different purposes, ranging from the creation of perpetual archives to creating research corpora that can be used for Music Information Retrieval (MIR) tasks and multidisciplinary approaches for the analysis of this music. The production workflow establishes a path for storing and accessing all the data gathered in these sessions.

Original languageEnglish (US)
Title of host publicationProceedings of DLfM 2023 - 10th International Conference on Digital Libraries for Musicology, In Association with ISMIR 2023
PublisherAssociation for Computing Machinery
Pages1-6
Number of pages6
ISBN (Electronic)9798400708336
DOIs
StatePublished - Nov 10 2023
Event10th International Conference on Digital Libraries for Musicology, DLfM 2023 - Milan, Italy
Duration: Nov 10 2023 → …

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Conference on Digital Libraries for Musicology, DLfM 2023
Country/TerritoryItaly
CityMilan
Period11/10/23 → …

Keywords

  • Arabian Gulf
  • Field recording
  • Methodologies
  • Traditional music

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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