The Classification and Recognition of Turkish Vowels with Self-Organizing Maps

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The easiness of putting the model into practice, and making signal or system dynamics and structure observable has made dynamic modeling for time series very popular for the last years. By the years, new versions and approaches of dynamic modeling have been developed and applied to different kind of signals and systems. Kohonen’s suggestion was a new approach to local dynamic modeling which he had offered in 1990. The new technique’s name was ‘Self Organizing Maps’. The innovation of the new approach was its needless of the memory for saving the history of time series. It was because the whole model is updated with the new sample of time series. New versions of this technique are introduced in a lot of different kinds of applications by the years. In this work, ‘Self Organizing Maps’ technique is applied to Turkish vowels and worked on the advantages of the technique.

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Self , Organising Maps , Local Dynamic Modelling , Speech Recognition.

Uludağ University Journal of The Faculty of Engineering

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Uludağ University Journal of The Faculty of Engineering