TY - GEN
T1 - Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
AU - Weninger, Felix
AU - Amir, Noam
AU - Amir, Ofer
AU - Ronen, Irit
AU - Eyben, Florian
AU - Schuller, Bjorn
PY - 2012
Y1 - 2012
N2 - We address the robustness of features for fully automatic recognition of vibrato, which is usually defined as a periodic oscillation of the pitch (F0) of the singing voice, in recorded polyphonic music. Using an evaluation database covering jazz, pop and opera music, we show that the extraction of pitch is challenging in the presence of instrumental accompaniment, leading to unsatisfactory classification accuracy (61.1 %) if only the F0 frequency spectrum is used as features. To alleviate, we investigate alternative functionals of F0, alternative low-level features besides F0, and extraction of vocals by monaural source separation. Finally, we propose to use inter-quartile ranges of F0 delta regression coefficients as features which are highly robust against pitch extraction errors, reaching up to 86.9% accuracy in real-life conditions without any signal enhancement.
AB - We address the robustness of features for fully automatic recognition of vibrato, which is usually defined as a periodic oscillation of the pitch (F0) of the singing voice, in recorded polyphonic music. Using an evaluation database covering jazz, pop and opera music, we show that the extraction of pitch is challenging in the presence of instrumental accompaniment, leading to unsatisfactory classification accuracy (61.1 %) if only the F0 frequency spectrum is used as features. To alleviate, we investigate alternative functionals of F0, alternative low-level features besides F0, and extraction of vocals by monaural source separation. Finally, we propose to use inter-quartile ranges of F0 delta regression coefficients as features which are highly robust against pitch extraction errors, reaching up to 86.9% accuracy in real-life conditions without any signal enhancement.
KW - Singing style
KW - feature extraction
KW - music signal processing
UR - http://www.scopus.com/inward/record.url?scp=84867592317&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2012.6287823
DO - 10.1109/ICASSP.2012.6287823
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AN - SCOPUS:84867592317
SN - 9781467300469
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 85
EP - 88
BT - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
T2 - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Y2 - 25 March 2012 through 30 March 2012
ER -