- From: Alo Allik <alo.allik@eecs.qmul.ac.uk>
- Date: Mon, 29 Apr 2013 14:41:44 +0100
- To: public-lod@w3.org
- Message-Id: <94DD967D-D0E0-4B42-AAFC-6E37941BA126@eecs.qmul.ac.uk>
Dear Linked Open Data community We have released 2 linked data resources developed during the SOVARR project at the Centre for Digital Music (Queen Mary University of London). Both of these resources contain information about features extracted from audio files. These audio features are commonly used in music information retrieval and research for various high level tasks, e.g. musical genre classification or querying a musical database by singing or humming. The published resources are: - a catalog of audio features compiled from literature, source code, online documents and existing linked data resources - a vocabulary of features which is a clean version of the catalog You can access these resources in HTML, RDF/XML and N3 formats. Catalog: http://sovarr.c4dm.eecs.qmul.ac.uk/af/catalog/1.0# Vocabulary: http://sovarr.c4dm.eecs.qmul.ac.uk/af/vocabulary/1.0# There is a blog post on the project website about the release: http://sovarr.c4dm.eecs.qmul.ac.uk/?q=node/258 It is likely that, in the present form, these resources are incomplete and may very well contain inconsistencies and errors. Therefore, we welcome any additions, corrections or suggestions you may have. Alo Allik, György Fazekas, Simon Dixon Shared Open Vocabulary for Audio Research and Retrieval (SOVARR) http://sovarr.c4dm.eecs.qmul.ac.uk Centre for Digital Music, Queen Mary University of London Mile End Rd, London E1 4NS, United Kingdom Email: alo.allik@eecs.qmul.ac.uk
Received on Monday, 29 April 2013 13:42:10 UTC