A Frobenius norm approach to glottal closure detection from the speech signal

The detection of glottal closure instants has been a necessary step in several applications of speech processing, such as voice source analysis, speech prosody manipulation and speech synthesis. The paper presents a new algorithm for glottal closure detection that compares favorably with other methods available in terms of robustness and computational efficiency. The authors propose to use the singular value decomposition (SVD) approach to detect the instants of glottal closure from the speech signal. The proposed SVD method amounts to calculating the Frobenius norms of signal matrices and therefore is computationally efficient. Moreover, it produces well-defined and reliable peaks that indicate the instants of glottal closure. Finally, with the introduction of the total linear least squares technique, two other proposed methods are reinvestigated and unified into the SVD framework