Algorithms for high order hidden Markov modelling

Date
1997
Authors
du Preez J.A.
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
We detail an algorithm that transforms any higher order hidden Markov model (HMM) to an equivalent first order HMM. This makes it possible to process higher order HMMs with standard techniques applicable to first order models. Based on this equivalence, a fast incremental algorithm is developed for training higher order HMMs from lower order approximations, thereby avoiding the training of redundant parameters. This makes training of high order HMMs practical for many applications.
Description
Keywords
Approximation theory, Markov processes, Mathematical models, Fast incremental algorithms, Hidden Markov model (HMM), Algorithms
Citation
Proceedings of the South African Symposium on Communications and Signal Processing, COMSIG