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We present a new method for the estimation of a continuous fundamental frequency (F0) contour. The algorithm implements a global optimization and yields virtually error-free F0 contours for high quality speech signals. Such F0 contours are subsequently used to extract a continuous fundamental wave. Some local properties of this wave, together with a number of other speech features allow to classify the frames of a speech signal into five classes: voiced, unvoiced, mixed, irregularly glottalized and silence. The presented F0 detection and frame classification can be applied to F0 modeling and prosodic modification of speech segments in high-quality concatenative speech synthesis.