Keywords: Field recordings, Data capture, Audio production, Music information retrieval, Audio metadata, Checklists


Field sound recordings are an indispensable source of data for ethnomusicologists. However, to my knowledge there are no standards or guidelines of how this data should be captured and managed. With the progress made in machine learning, it has become vital to record data in a way that also supports the retrieval of information about the music. This article describes a model developed for field recordings that aims to aid an objective data gathering process. This model, developed through an action research process that spanned multiple field recording sessions from 2009–2015, include recording equipment, production processes, the gathering of metadata as well as intellectual property rights. The core principles identified in this research are that field recording systems should be designed to provide accurate feedback as a means of quality control and should capture and manage metadata without relying on secondary tools. The major findings are presented in the form of a checklist that can serve as a point of departure for ethnomusicologists making field recordings.

Author Biography

Gerhard Roux, Stellenbosch University, South Africa
Gerhard Roux is a lecturer in music technology at Stellenbosch University, South Africa, and a recording technician that specialises in natural acoustic audio recordings and surround sound production for film. In pursuit of a signature sound, Gerhard designs and builds ribbon microphones. Gerhard’s research focuses on managing the complex adaptive nature of audio production systems with a particular focus on socio-technical interface in creative environments.