Design And Building Of The Handwriting Uyghur Words Recognition Based On HTK

Online handwriting character recognition plays an important role in the field ofpattern recognition, having a large value both in theory and practical application. Atpresent, the recognition research is focus on English, Chinese and other widely usedcharacters at home and abroad, and it has made great achievements applied to real life.Fewer studies on minority characters, online handwriting Uyghur characterrecognition has been focused on the letters, however the research for wordsrecognition is still in the stage of exploration. This paper aims to propose sometechniques and methods for online handwriting Uighur word recognition.Uyghur script is similar to Arabic. Learning from the mature method about Arabic,English and other commonly used characters, this paper presents a method based onHMMs using HTK. It is in line with Uyghur word characteristics. This paper firstlyanalyzes the difficulties of the Uyghur character recognition, and describes the basicprinciples of the Hidden Markov Model, the three problems and their algorithm.Secondly, it gives an overview of the establishment for the sample set and proposessome methods about preprocessing and feature extraction for Uyghur word. Inaddition, there have some work on delay strokes handing, which adopting theprojection method. Thirdly, it analyzes the structure of HMM model and differentlanguage models in detail. Rule-based language model exclude the possible wordwhich is not in accordance with the structure of Uyghur word, and improves therecognition rate. Finally, HMMs are initialized, trained. Words are identified, assessed.They are both using HTK tools. It has some experimental comparison, summarizingthe advantages and disadvantages of different language models. The experimentalresults show that the method proposed in this paper is practicable and effective.