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20 Years of Automatic Chord Recognition from Audio

Authors: Johan Pauwels; Ken O'Hanlon; Emilia Gómez; Mark B. Sandler;

20 Years of Automatic Chord Recognition from Audio

Abstract

In 1999, Fujishima published Realtime Chord Recognition of Musical Sound: a System using Common Lisp Music. This paper kickstarted an active research topic that has been popular in and around the ISMIR community. The field of Automatic Chord Recognition (ACR) has evolved considerably from early knowledge-based systems towards data-driven methods, with neural network approaches arguably being central to current ACR research. Nonetheless, many of its core issues were already addressed or referred to in the Fujishima paper. In this paper, we review those twenty years of ACR according to these issues. We furthermore attempt to frame current directions in the field in order to establish some perspective for future research.

Comunicació presentada a: 20th annual conference of the International Society for Music Information Retrieval (ISMIR) celebrat del 4 al 8 de novembre de 2019 a Delft, Països Baixos.

This work has been funded by the UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/L019981/1.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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