面向手语信息处理的维吾尔文本采集的研究

Research on Uyghur text acquisition for sign language information processing

从自然语言处理以及深度学习的基本理念、原则出发,为基于中国手语的维吾尔文本信息处理研究提供数据资源,为面向手语信息的手语合成研究,为手语新闻文本编辑研究提供科学依据,对维吾尔文本进行自动分词、自动分句研究,并利用Word2Vec方法进一步建立文本词元库,通过这样保证训练语料的多元化及通用性。最后,利用词干提取方法以及分割字母的方式将维吾尔文本信息转换成手语文本信息,并在此基础上初步采集面向手语信息处理的维吾尔文本信息。实验表明该研究达到了预期目标。

Proceeding from the basic concepts and principles of natural language processing and deep learning,research on automatic word and sentence segmentation is conducted for the Uyghur text,so as to provide data resources for Uyghur text information processing research based on Chinese sign language,and scientific basis for research on sign language synthesis and sign language news text editing based on sign language information. The Word2Vec method is used to further establish the text word element library,so as to ensure the diversity and universality of training corpus. The Uyghur text information is converted into the sign language text information by using the methods of word stem extraction and letter segmentation. On this basis,the Uyghur text information based on sign language processing is initially collected. The experimental results show that the research can achieve the expected research goal.