In state mixture modelling (SMM), the temporal structure of the observation sequences is represented by the state joint probability distribution where mixtures of states are considered. This technique is considered in an iterative scheme via maximum likelihood estimation. A fuzzy estimation approach is also introduced to cooperate with the SMM model. This new approach not only saves calculations from 2NTT (HMM direct calculation) and N2T (Forward-backward algorithm) to just only 2NT calculations, but also achieves a better recognition result.
|Number of pages||8|
|Journal||Pattern Recognition Letters|
|Publication status||Published - Nov 1999|
|Event||Proceedings of the 1999 Pattern Recognition in Practice (PRP VI) - Vlieland, Neth|
Duration: 2 Jun 1999 → 4 Jun 1999