Automatic glottal closed-phase location and analysis by Kalman filtering

In an effort to develop techniques that enhance data-driven techniques in speaker characterisation for speech synthesis, this paper describes a method for automatically determining the location of the closed phase (CP) of the glottal cycle, with subsequent linear predictive (LP) analysis on the CP speech data. Our approach to detecting the CP is designed with the intention of excluding intervals that are not within the CP rather that accurately locating the instants of glottal closure and opening. The indicator used is the log determinant of the Kalman filter (KF) estimate error covariance matrix. The CP LP analysis applies a Kalman filter to the CP data only by treating the openphase data as “missing” and harnessing the non-independence of neighbouring CP spectra. The Kalman filtering process in both techniques is refined to accommodate smoothing, Kalman parameter re-estimation, handling of missing data, and estimation robustification.

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