Automatic Chord Estimation from Audio: A Review of the State of the Art

Authors:
Matt McVicar;Raul Santos-Rodriguez; Yizhao Ni; Tijl De Bie
Affiliations:
Dept. of Eng. Math., Univ. of Bristol, Bristol, UK;Dept. of Eng. Math., Univ. of Bristol, Bristol, UK;Dept. of Eng. Math., Univ. of Bristol, Bristol, UK;Dept. of Eng. Math., Univ. of Bristol, Bristol, UK
Venue:
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Year:
2014

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Abstract

In this overview article, we review research on the task of Automatic Chord Estimation (ACE). The major contributions from the last 14 years of research are summarized, with detailed discussions of the following topics: feature extraction, modeling strategies, model training and datasets, and evaluation strategies. Results from the annual benchmarking evaluation Music Information Retrieval Evaluation eXchange (MIREX) are also discussed as well as developments in software implementations and the impact of ACE within MIR. We conclude with possible directions for future research.