ISCA Tutorial and Research Workshop on Statistical and Perceptual Audition (SAPA2008)

Brisbane, Australia
September 21, 2008

Singing Voice Detection using Modulation Frequency Feature

Maria Markaki (1,2), Andre Holzapfel (1,2), Yannis Stylianou (1,2)

(1) Computer Science Department, University of Crete, Greece
(2) Institute of Computer Science, FORTH, Greece

In this paper, a feature set derived from modulation spectra is applied to the task of detecting singing voice in historical and recent recordings of Greek Rembetiko. A generalization of SVD to tensors, Higher Order SVD (HOSVD), is applied to reduce the dimensions of the feature vectors. Projection onto the "significant" principal axes of the acoustic and modulation frequency subspaces, results in a compact feature set, which is evaluated using an SVM classifier on a set of hand labeled musical mixtures. Fusion of the proposed features with MFCCs and delta coefficients reduces the optimal detection cost from 11.11% to 9.01%.

Full Paper

Bibliographic reference.  Markaki, Maria / Holzapfel, Andre / Stylianou, Yannis (2008): "Singing voice detection using modulation frequency feature", In SAPA-2008, 7-10.