Markovian Models for Sequential Data

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A survey on off-line Cursive Word Recognition (2002, background): “[43,46] and for their speci/c use in handwriting recognition see Ref.”
A Novel Connectionist System for Unconstrained Handwriting Recognition (2009, methodology): “A more successful use of neural networks for handwriting recognition has been to combine them with HMMs in the so-called hybrid approach [22], [23].”
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks (2006, unknown): “At present, the most eﬀective use of RNNs for sequence labelling is to combine them with HMMs in the so-called hybrid approach (Bourlard & Morgan, 1994; Bengio., 1999).”
Sigma-point kalman filters for probabilistic inference in dynamic state-space models (2004, methodology): “For this specific form of the state-space, the DSSM is known as a hidden Markov model (HMM) [14].”
Survey of clustering algorithms (2005, background): “More recent advances on HMMs and other related topics are reviewed in [30].”
Supervised Sequence Labelling with Recurrent Neural Networks (2012, methodology): “However, we will frequently refer to the well-known generative method hidden Markov models (Rabiner, 1989; Bengio, 1999).”