September 22-25, 1997
The aim of the research described in this paper is to overcome the modeling limitation of conventional hidden Markov models. We present a segmental model that consists of two elements. The first is a nonparametric representation of both the mean and variance trajectories, which describes the local dynamics. The second element is some parameterized transformation (e.g., random shift) of the trajectory that is global to the segment and models long-term variations such as speaker identity.
Bibliographic reference. Goldberger, Jacob / Burshtein, David / Franco, Horacio (1997): "Segmental modeling using a continuous mixture of non-parametric models", In EUROSPEECH-1997, 1195-1198.