CUED Publications database

Competitive training in hidden Markov models

Young, SJ (1990) Competitive training in hidden Markov models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2. pp. 681-684. ISSN 0736-7791

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The use of hidden Markov models is placed in a connectionist framework, and an alternative approach to improving their ability to discriminate between classes is described. Using a network style of training, a measure of discrimination based on the a posteriori probability of state occupation is proposed, and the theory for its optimization using error back-propagation and gradient ascent is presented. The method is shown to be numerically well behaved, and results are presented which demonstrate that when using a simple threshold test on the probability of state occupation, the proposed optimization scheme leads to improved recognition performance.

Item Type: Article
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:52
Last Modified: 22 May 2018 08:06