Dig that lick: Analysing large-scale data for melodic patterns in jazz performances.

Abstract

The recorded legacy of jazz spans a century and provides a vast corpus of data documenting its development. Recent advances in digital signal processing and data analysis technologies enable automatic recognition of musical structures and their linkage through metadata to historical and social context. Automatic metadata extraction and aggregation give unprecedented access to large collections, fostering new interdisciplinary research opportunities. This project aims to develop innovative technological and music-analytical methods to gain fresh insight into jazz history by bringing together renowned scholars and results from several high-profile projects. Musicologists and computer scientists will together create a deeper and more comprehensive understanding of jazz in its social and cultural context. We exemplify our methods via a full cycle of analysis of melodic patterns, or "licks," from audio recordings to an aesthetically contextualised and historically situated understanding.

Principal Investigators

Simon Dixon, Queen Mary University of London, United Kingdom, AHRC/ESRC
Hélène Papadopoulos, National Center for Scientific Research, France, ANR
Martin Pfleiderer, University of Music Franz Liszt Weimar, Germany, DFG
Gabriel Solis, University of Illinois, United States, NEH