Switching Linear Dynamical Systems for Speech Recognition

@inproceedings{Rosti2003SwitchingLD,
  title={Switching Linear Dynamical Systems for Speech Recognition},
  author={A-V. I. Rosti and Mark J. F. Gales},
  year={2003}
}
This paper describes the application of Rao-Blackwellised Gibbs sampling (RBGS) to speech recognition using switching linear dynamical systems (SLDSs) as the acoustic model. The SLDS is a hybrid of standard hidden Markov models (HMMs) and linear dynamical systems. It is an extension of the stochastic segment model (SSM) where segments are assumed independent. SLDSs explicitly take into account the strong co-articulation present in speech using a Gauss-Markov process in a low dimensional, latent… CONTINUE READING
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