Output details
11 - Computer Science and Informatics
Robert Gordon University
Output title
Music-inspired texture representation
Type
E - Conference contribution
DOI
-
Name of conference/published proceedings
AAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence
Volume number
1
Issue number
-
First page of article
52
ISSN of proceedings
-
Year of publication
2012
Number of additional authors
2
Additional information
This paper was accepted for oral presentation at this highly selective international AI conference (11.5% acceptance [AAAI Preface]). Its significance comes from the Mel-Frequency Spectrum (MFS) texture representation for music content that overcomes a speech bias in standard MFCC. A theoretical analysis of MFCC reveals loss of information at important parts of the note spectrum, addressed in the novel MFS. A rigorous evaluation using a large music collection demonstrates the advantage of MFS over several MFCC variants for music recommenders. Subsequently, QMUL’s Centre for Digital Music invited the authors to add an MFS plugin to QMVamp (www.vamp-plugins.org/download.html).
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
