Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Hybrid music information retrieval

Hybrid music information retrieval Int J Multimed Info Retr (2013) 2:1–2 DOI 10.1007/s13735-013-0033-9 EDITORIAL Preface to the special issue Peter Knees · Markus Schedl · Òscar Celma Published online: 5 February 2013 © Springer-Verlag London 2013 In the past decade, research in Music Information Retrieval novel algorithms enable applications that capture musical (MIR) has created a wealth of methods to extract latent musi- aspects on a more comprehensive level than content or cal information from the audio signal. While these meth- context-based approaches alone. Exploiting the full range ods are capable to infer acoustic similarities between music of MIR technology, for instance, innovative user interfaces pieces, to reveal a song’s structure, or to identify a piece from to access the large amounts of music available today (e.g., a noisy recording, they cannot capture semantic information on tablets or smart mobile devices), or context-aware music that is not encoded in the audio signal, but is nonetheless recommendation systems are conceivable. essential to many listeners. For instance, the meaning of a This Special Issue on “Hybrid Music Information song’s lyrics, the background of a singer, or the work’s histor- Retrieval” highlights the newest developments in combining ical context cannot be derived without additional meta-data. music http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Multimedia Information Retrieval Springer Journals

Hybrid music information retrieval

Download PDF
2 pages

Loading next page...
 
/lp/springer-journals/hybrid-music-information-retrieval-lflLppnFrw
Publisher
Springer Journals
Copyright
Copyright © 2013 by Springer-Verlag London
Subject
Computer Science; Multimedia Information Systems; Information Storage and Retrieval; Information Systems Applications (incl. Internet); Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Computer Science, general
ISSN
2192-6611
eISSN
2192-662X
DOI
10.1007/s13735-013-0033-9
Publisher site
See Article on Publisher Site

Abstract

Int J Multimed Info Retr (2013) 2:1–2 DOI 10.1007/s13735-013-0033-9 EDITORIAL Preface to the special issue Peter Knees · Markus Schedl · Òscar Celma Published online: 5 February 2013 © Springer-Verlag London 2013 In the past decade, research in Music Information Retrieval novel algorithms enable applications that capture musical (MIR) has created a wealth of methods to extract latent musi- aspects on a more comprehensive level than content or cal information from the audio signal. While these meth- context-based approaches alone. Exploiting the full range ods are capable to infer acoustic similarities between music of MIR technology, for instance, innovative user interfaces pieces, to reveal a song’s structure, or to identify a piece from to access the large amounts of music available today (e.g., a noisy recording, they cannot capture semantic information on tablets or smart mobile devices), or context-aware music that is not encoded in the audio signal, but is nonetheless recommendation systems are conceivable. essential to many listeners. For instance, the meaning of a This Special Issue on “Hybrid Music Information song’s lyrics, the background of a singer, or the work’s histor- Retrieval” highlights the newest developments in combining ical context cannot be derived without additional meta-data. music

Journal

International Journal of Multimedia Information Retrieval – Springer Journals

Published: Feb 5, 2013

There are no references for this article.