Journal paper on the QUARTET dataset and the Repovizz system

Journal paper on the QUARTET dataset and the Repovizz system



Over the past few years, there has been an increasingly active discussion about publishing and accessing datasets for reuse in academic research. Although sometimes driven by concrete needs concerning a particular dataset or project, this topic is not accessory. In a data-driven research community like ours, it is very healthy to exchange ideas and perspectives on how to devise flexible means for making our data and results accessible--a valuable pursuit towards supporting research reproducibility.

The Music Technology Group of UPF hosts and provides free access to a number of datasets for music and audio research. As it normally happens with other published datasets, one needs to download the data files and procure means for exploring them locally. If limited to audio files or annotations, such process does not generally bring significant difficulties other than data volume. However, as the number and nature of modalities, extracted descriptors, and annotations increase (think of motion capture, video, physiological signals, time series of different sample rates, etc.), difficulties arise not only in the design or adoption of formatting schemes, but also in the availability of platforms that enable and facilitate exchange by providing simple ways to remotely visualize or explore the data before downloading.

In the context of several recent projects focused on music performance analysis and multimodal interaction, we had to collect, process, and annotate music performance recordings that included dense data streams of different modalities. Envisioning the future release of our dataset for the research community, we realized the need for better means to explore and exchange data. Since then, at UPF we have been developing Repovizz, a remote hosting platform for multimodal data storage, visualization, annotation, and selective retrieval via a web interface and a dedicated API.

By way of the recently published article E. Maestre, P. Papiotis, M. Marchini, Q. Llimona, O. Mayor, A. Pérez, M. Wanderley, Enriched Multimodal Representations of Music Performances: Online Access and Visualization IEEE MultiMedia, Vol 24:1, pp. 24-34, 2017, we introduce Repovizz to the MIR Community and open access to the QUARTET dataset, a fully annotated collection of string quartet multimodal recordings released through Repovizz.

For a short, unadorned video demonstrating Repovizz, please go to Although still under development, Repovizz can be used by anyone in the academic community.

The QUARTET dataset comprises 96 recordings of string quartet exercises involving solo and ensemble conditions, containing multichannel audio (ambient microphones and piezoelectric pickups), video, motion capture (optical and magnetic) of instrumental gestures and of musician upper bodies, computed bowing gesture signals, extracted audio descriptors, and multitrack score-performance alignment. The dataset, processed and curated over the past years partly in the context of the PhD dissertation work of Panos Papiotis on ensemble interdependence, is now freely available for the research community.