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Information theory principles for the design of self-organizing maps in combination with hidden Markov modeling for continuous speech recognition

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1 Author(s)

Resulting from that combination is the aspect of designing the map using different rules from those usually mentioned in the standard literature for modifying the environment and the adaptation gain during learning. This can be explained by the fact that hidden Markov modeling is an information-theory approach, and the combination of self-organizing maps with MHH implies the use of information-theory principles also for the design of the map leading to the modified requirements for the learning procedure mentioned above. It is shown that substantial improvements can be obtained if the design principles presented are used

Published in:

Neural Networks, 1990., 1990 IJCNN International Joint Conference on

Date of Conference:

17-21 June 1990