Global Music Database

Ecological sustainable solutions for online media in complex networks

The future of music is digital. The increasing digitalization and networking of the world has affected the way we use, store and make music. In 2012, the amount of digital music files will outnumber the amount of musical pieces on physical sound carriers.

The worldwide availability of digital music creates the challenge of organizing and describing this huge amount of data so that single musical pieces, genres and cultures can be easily and adequately identified. In the absence of the musicians, of CD covers, that is, of the possibility of gathering extra information about the music one listens to, engines must be developed for retrieving musical information from the music itself. That is exactly the task of MIR - Music Information Retrieval –, to develop software learning to interpret sound signals just like humans do.

To know which kind of music someone is listening to will no longer need manually added tags, but, instead, will be automatically recognized through its musical attributes. This is not only an advantage for the users but also for the providers of the worldwide networks. An enhanced search engine will dramatically decrease the data bandwidth because a more specific query will decrease the useless data downloads caused by misleading filenames or tags. This way bandwidth, server capacity and hence energy is saved.

However, how can the different musics of our world be translated into one sole language, which both musicologists from different cultures as well as an engine would understand?

The project Global Music Database aims to develop a computer-based music analysis engine, which should automatically recognize and classify music genres worldwide. Therefore the musicologists of the University of Music FRANZ LISZT Weimar work closely together with digital audio engineers from Bach Technology and from the Institute of Digital Media Technology (IDMT) Fraunhofer Ilmenau, striving for a common approach of understanding and analyzing the most different musical styles, from traditional to pop. 26 musicologists and music experts from many regions of the world are joined together to select the most typical musical samples and characteristics of their cultures.

This project provides the possibility of a worldwide discussion, comparison and understanding of music with a common goal: the collection and automatic analysis of musical information.



Team

Head of Research
Prof. Dr. Tiago de Oliveira Pinto
transmusic(at)hfm-weimar.de

Project Coordinator
Philip Küppers
philip.kueppers(at)hfm-weimar.de

Music Analysis
Nina Graeff
nina.graeff(at)hfm-weimar.de

Systemic Musicology/Computer Science
Felix Pfeifer
felix.pfeifer(at)hfm-weimar.de


Research on Rhythm

Africa
Dr. Moya Aliya Malamusi
Yohana Malamusi

Arab World
Mohamad Alfaham

Asia
Prof. Dr. Jin-Ah Kim (Team Coordinator Asia)
Prof. Dr. Jun Yon Hwang (Team Coordinator Eastasia)
Ji-ye Jeon
Yu-seok Kim
Ran-kyoung Lim

Balkans
Martha Stellmacher

India
Prashant Kumar Mallick

Latinamerica
Friederike Jurth
Nicholas Dieter Berdaguer Rauschenberg
Alan Riedel
Brunela Succi

Northamerica/Europe
Jörg Holdinghausen
Marvin Mügge
Stefan Wittich
Christian Vinne

Turkey
Nevzat Çiftçi

Research on Vocal

Katja Lehmann
Ann-Paulin Steigerwald


Research Assistant Media Data
Vanessa Zuber

Editorial Department Homepage
Susanne Schmieder

Partners

Events

  • 5.-7. September 2011, Weimar: Workshop "The Genre Issue in MIR"
  • 13.-15. October 2011, Weimar: Symposium "Musikwirtschaft 2.0 – Perspektiven für die Musik"
Prof. Tiago de Oliveira Pinto, Philip Küppers: "Globale Musikdatenbank: Eine Kooperation zwischen Musikwissenschaft, Audio- und Umwelttechnologie"
  • 1.-5. November 2011, Weimar: Internationales Symposium "Musik als Kulturerbe. Shashmaqom. Die Klassische Musik Mittelasiens"
Philip Küppers: "The Importance of Digitalization for the Documentation and Promotion of the Musical Cultural Heritage"

  • 25. November 2011, Weimar: Research Symposium "Transcultural Music Studies"
Felix Pfeifer: „Mikrorhythmusanalyse mit akustischen Kameras”