Projects per year
Abstract
Systems built using deep learning neural networks trained on low-level spectral periodicity features (DeSPerF) reproduced the most “ground truth” of the systems submitted to the MIREX 2013 task, “Audio Latin Genre Classification.” To answer why this was the case, we take a closer look at the behavior of a DeSPerF system we create and evaluate using the benchmark dataset BALLROOM. We find through time stretching that this DeSPerF system appears to obtain a high figure of merit on the task of music genre recognition because of a confounding of tempo with “ground truth” in BALLROOM. This observation motivates several predictions.
Original language | English |
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Title of host publication | Proceedings of 4th International Workshop on Cognitive Information Processing (CIP 2014) |
Editors | Lars Kai Hansen, Søren Holdt Jensen, Jan Larsen |
Number of pages | 6 |
Volume | 1 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Publication date | 2014 |
Pages | 1-6 |
ISBN (Print) | 978-1-4799-3696-0 |
DOIs | |
Publication status | Published - 2014 |
Event | International Workshop on Cognitive Information Processing - Bella Sky Hotel, Copenhagen, Denmark Duration: 26 May 2014 → 28 May 2014 |
Conference
Conference | International Workshop on Cognitive Information Processing |
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Location | Bella Sky Hotel |
Country/Territory | Denmark |
City | Copenhagen |
Period | 26/05/2014 → 28/05/2014 |
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Dive into the research topics of 'A Closer Look at Deep Learning Neural Networks with Low-level Spectral Periodicity Features'. Together they form a unique fingerprint.Projects
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CoSound
Christensen, M. G. (Project Participant), Tan, Z.-H. (Project Participant), Jensen, S. H. (Project Participant) & Sturm, B. L. (Project Participant)
01/01/2012 → 31/12/2015
Project: Research