Dig That Lick: Analysing Large-scale Data for Melodic Patterns in Jazz Performances
Supported by the German Research Foundation (DFG)
run-time: 2 years, beginning 10/1/2017
Homepage: http://dig-that-lick.eecs.qmul.ac.uk/
The Project is part of the DIGGING INTO DATA CHALLENGE 2017
https://diggingintodata.org/awards/2016/project/dig-lick-analysing-large-scale-data-melodic-patterns-jazz-performances
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 the 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.
run-time: 2 years, beginning 10/1/2017
Homepage: http://dig-that-lick.eecs.qmul.ac.uk/
The Project is part of the DIGGING INTO DATA CHALLENGE 2017
https://diggingintodata.org/awards/2016/project/dig-lick-analysing-large-scale-data-melodic-patterns-jazz-performances
- Simon Dixon (PI), Queen Mary University of London, UK
- Krin Gabbard, Columbia University, USA
- Hélène Papadopoulos, National Center for Scientific Research (CNRS), France
- Geoffroy Peeters, Institute for Research and Coordination in Acoustics/Music (IRCAM), France
- Martin Pfleiderer, University of Music Franz Liszt, Weimar, Germany
- Gabriel Solis, University of Illinois Champaign Urbana, USA
- Tillman Weyde, City University of London, UK
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 the 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.
Leitung Teilprojekt Weimar
Wissenschaftliche Mitarbeiter
Dr. Klaus Frieler
Frank Höger, MA