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Appl. Sci. 2016, 6(5), 157; doi:10.3390/app6050157

Chord Recognition Based on Temporal Correlation Support Vector Machine

1
School of Electronic Information Engineering, Tianjin University, Tianjin 30072, China
2
School of Information Science and Electronic Engineering, Shandong Jiaotong University, Ji’nan 250357, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vesa Valimaki
Received: 11 February 2016 / Revised: 6 May 2016 / Accepted: 6 May 2016 / Published: 19 May 2016
(This article belongs to the Special Issue Audio Signal Processing)
View Full-Text   |   Download PDF [1977 KB, uploaded 19 May 2016]   |  

Abstract

In this paper, we propose a method called temporal correlation support vector machine (TCSVM) for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and the sparse component to contain the vocal signals. Then, we extract a new logarithmic pitch class profile (LPCP) feature called enhanced LPCP from the low-rank part. To exploit the temporal correlation among the LPCP features of chords, we propose an improved support vector machine algorithm called TCSVM. We perform this study using the MIREX’09 (Music Information Retrieval Evaluation eXchange) Audio Chord Estimation dataset. Furthermore, we conduct comprehensive experiments using different pitch class profile feature vectors to examine the performance of TCSVM. The results of our method are comparable to the state-of-the-art methods that entered the MIREX in 2013 and 2014 for the MIREX’09 Audio Chord Estimation task dataset. View Full-Text
Keywords: music information retrieval; hidden Markov models; robust principal component analysis; pitch class profile; chord estimation music information retrieval; hidden Markov models; robust principal component analysis; pitch class profile; chord estimation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rao, Z.; Guan, X.; Teng, J. Chord Recognition Based on Temporal Correlation Support Vector Machine. Appl. Sci. 2016, 6, 157.

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