摘要
提出一种维吾尔文手写整词识别方法,通过拼接单词中各连体段的特征构建单词的特征向量,用K-means聚类算法对连体段进行聚类操作降低单词特征向量的维度并输出离散的数字序列,通过隐马尔科夫模型完成单词的建模和识别。
Illustrates a recognition method to Uyghur whole word, constructs the word feature vector by splicing feature of each segment in words, then reduces the dimension of the feature vector and output word discrete sequence of numbers by K-means algorithm, completes the modeling and identification of words by using hidden Markov model.
