Cursive Letters Language Processing: Muqla Model and Toeplitz Matrices Approach
This article presents a new model (based on Muqla idea) used in recognition of cursive letters. It is used for creating feature vectors based on Toeplitz matrices. As the approach is used for the first time, no comparison had been made from modelling point of view. However, the way of feature vectors extraction in this approach showed its simplicity and may find its practical applications in processing and verifying both written and spoken texts. The suggested algorithm makes it possible to reduce the limiting factors  in recognition as it is easy to extend it to cover more vocabulary, syntax or semantic information.
KeywordsCharacteristic Vector Automatic Speech Recognition Toeplitz Matrice Suggested Algorithm Human Language Technology
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