THE HARMONIX SET: BEATS, DOWNBEATS, AND FUNCTIONAL SEGMENT ANNOTATIONS OF WESTERN POPULAR MUSIC Oriol Nieto1 Matthew McCallum1 Matthew E. P. Davies2 Andrew Robertson3 Adam Stark4 Eran Egozy5 1 Pandora Media, Inc., Oakland, CA, USA 2 INESC TEC, Porto, Portugal 3 Ableton AG, Berlin, Germany 4 MI·MU, London, UK 5 MIT, Cambridge, MA, USA
[email protected] ABSTRACT posed [2,11,25], the amount of human annotated data con- taining the three of them for a single collection is scarce. We introduce the Harmonix set: a collection of annotations This limits the training potential of certain methods, espe- of beats, downbeats, and functional segmentation for over cially those that require large amounts of information (e.g., 900 full tracks that covers a wide range of western popular deep learning [18]). music. Given the variety of annotated music information In this paper we present the Harmonix set: human an- types in this set, and how strongly these three types of data notations of beats, downbeats, and functional segmentation are typically intertwined, we seek to foster research that for 912 tracks of western popular music. These annotations focuses on multiple retrieval tasks at once. The dataset in- were gathered with the aim of having a significant amount cludes additional metadata such as MusicBrainz identifiers of data to train models to improve the prediction of such to support the linking of the dataset to third-party informa- musical attributes, which would later be applied to various tion or audio data when available. We describe the method- products offered by Harmonix, a video game company that ology employed in acquiring this set, including the annota- specializes in musically-inspired games.