A geometrical fuzzy clustering-based solution to glottal wave estimation
Yair Shapira, Isak Gath · The Journal of the Acoustical Society of America · 1998
Accurate estimation of the glottal waveform (GW) is required for purposes such as natural speech synthesis, speaker recognition, physiological speech processing, etc. Most methods available for GW estimation are based on inverse filtering of the speech signal through the vocal tract, and they all suffer from inaccuracies due to incorrect assumptions. The method for GW estimation developed in the present study is based on fuzzy clustering of quasi-linear geometrical substructures, represented within the signal shifts hyperspace. Algorithms for estimation of the driving function to the vocal tract are presented and evaluated on simulated and real data. Comparison of the fuzzy clustering-based method with the PSIAIF and Wong’s closed-phase algorithms shows that the present method is superior with respect to both the GW estimation and determination of GW event time instants.