Conference proceeding
MODELING MUSICAL RHYTHM AT SCALE WITH THE MUSIC GENOME PROJECT
2015 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA)
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
01 Jan 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Musical meter and attributes of the rhythmic feel such as swing, syncopation, and danceability are crucial when defining musical style. However, they have attracted relatively little attention from the Music Information Retrieval (MIR) community and, when addressed, have proven difficult to model from music audio signals. In this paper, we propose a number of audio features for modeling meter and rhythmic feel. These features are first evaluated and compared to timbral features in the common task of ballroom genre classification. These features are then used to learn individual models for a total of nine rhythmic attributes covering meter and feel using an industrial-sized corpus of over one million examples labeled by experts from Pandora (R) Internet Radio's Music Genome Project (R). Linear models are shown to be powerful, representing these attributes with high accuracy at scale.
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Details
- Title
- MODELING MUSICAL RHYTHM AT SCALE WITH THE MUSIC GENOME PROJECT
- Creators
- Matthew Prockup - Drexel Univ, ECE Dept, 3141 Chestnut St, Philadelphia, PA 19104 USAAndreas F. Ehmann - Pandora Media Inc, Oakland, CA 94612 USAFabien Gouyon - Pandora Media Inc, Oakland, CA 94612 USAErik M. Schmidt - Pandora Media Inc, Oakland, CA 94612 USAYoungmoo E. Kim - Drexel Univ, ECE Dept, 3141 Chestnut St, Philadelphia, PA 19104 USAIEEE
- Publication Details
- 2015 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA)
- Series
- IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
- Publisher
- IEEE
- Number of pages
- 5
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Identifiers
- 991019170474504721
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InCites Highlights
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- Web of Science research areas
- Acoustics
- Engineering, Electrical & Electronic