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Main Title: Beat histogram features from NMF-based novelty functions for music classification
Author(s): Lykartsis, Athanasios
Wu, Chih-Wei
Lerch, Alexander
Type: Conference Object
Is Part Of: 10.14279/depositonce-9530
Language Code: en
Abstract: In this paper we present novel rhythm features derived from drum tracks extracted from polyphonic music and evaluate them in a genre classification task. Musical excerpts are analyzed using an optimized, partially fixed Non-Negative Matrix Factorization (NMF) method and beat histogram features are calculated on basis of the resulting activation functions for each one out of three drum tracks extracted (Hi-Hat, Snare Drum and Bass Drum). The features are evaluated on two widely used genre datasets (GTZAN and Ballroom) using standard classification methods, concerning the achieved overall classification accuracy. Furthermore, their suitability in distinguishing between rhythmically similar genres and the performance of the features resulting from individual activation functions is discussed. Results show that the presented NMF-based beat histogram features can provide comparable performance to other classification systems, while considering strictly drum patterns.
Issue Date: 2015
Date Available: 21-Feb-2020
DDC Class: 780 Musik
Subject(s): Non-Negative Matrix Factorization
drum patterns
genre classification
beat histogram
Proceedings Title: Proceedings of the 16th International Society for Music Information Retrieval Conference
Editor: Müller, Meinard
Wiering, Frans
Publisher: International Society for Music Information Retrieval
Publisher Place: [S.l.]
Page Start: 434
Page End: 440
ISBN: 987-84-606-8853-2
Appears in Collections:FG Audiokommunikation » Publications

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