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Beat Tracking with a Cepstroid Invariant Neural Network
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Music Acoustics.ORCID iD: 0000-0002-4957-2128
2016 (English)In: 17th International Society for Music Information Retrieval Conference (ISMIR 2016), International Society for Music Information Retrieval , 2016, 351-357 p.Conference paper (Refereed)
Abstract [en]

We present a novel rhythm tracking architecture that learns how to track tempo and beats through layered learning. A basic assumption of the system is that humans understand rhythm by letting salient periodicities in the music act as a framework, upon which the rhythmical structure is interpreted. Therefore, the system estimates the cepstroid (the most salient periodicity of the music), and uses a neural network that is invariant with regards to the cepstroid length. The input of the network consists mainly of features that capture onset characteristics along time, such as spectral differences. The invariant proper-ties of the network are achieved by subsampling the input vectors with a hop size derived from a musically relevant subdivision of the computed cepstroid of each song. The output is filtered to detect relevant periodicities and then used in conjunction with two additional networks, which estimates the speed and tempo of the music, to predict the final beat positions. We show that the architecture has a high performance on music with public annotations. 

Place, publisher, year, edition, pages
International Society for Music Information Retrieval , 2016. 351-357 p.
Keyword [en]
Beat Tracking
National Category
Computer Science Other Computer and Information Science
Research subject
Speech and Music Communication
Identifiers
URN: urn:nbn:se:kth:diva-195348OAI: oai:DiVA.org:kth-195348DiVA: diva2:1044322
Conference
17th International Society for Music Information Retrieval Conference (ISMIR 2016); New York City, USA, 7-11 August, 2016.
Funder
Swedish Research Council, 2012 - 4685
Note

QC 20161107

Available from: 2016-11-02 Created: 2016-11-02 Last updated: 2016-11-14Bibliographically approved

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Beat Tracking with a Cepstroid Invariant Neural Network(535 kB)17 downloads
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Elowsson, Anders
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