建立音节数据库解决高棉语分词问题
Building a Syllable Database to Solve the Problem of Khmer Word Segmentation
摘要：
分词是自然语言处理中的一个基本问题。由于语言具有复杂的书写系统，如越南南部的高棉语，这个问题确实非常棘手，构成了重大挑战。虽然越南以及国际上的一些专家对这一问题进行了深入的研究，但迄今为止，在高棉语处理过程中，仍然没有达到要求的合理结果，特别是没有对歧义现象进行彻底的处理。本文提出了一种基于双音节模型的音节划分方法，从而建立高棉语音节数据库，但目前还没有实际应用。该方法使用从在线高棉语词典更新的词汇数据库和一些支持的词典充当训练数据和补充语言特征。每一个组成部分集群标记和定位的第一个和最后一个字母，以确定整个音节。该方法切实可行，测试结果准确率高，消除了歧义，有助于解决高棉语分词问题，提高高棉语处理的应用效率。
英文摘要：
Word segmentation is a basic problem in natural language processing. With the languages having the complex writing system like the Khmer language in Southern of Vietnam, this problem really very intractable, posing the significant challenges. Although there are some experts in Vietnam as well as international having deeply researched this problem, there are still no reasonable results meeting the demand, in particular, no treated thoroughly the ambiguous phenomenon, in the process of Khmer language processing so far. This paper present a solution based on the syllable division into component clusters using two syllable models proposed, thereby building a Khmer syllable database, is still not actually available. This method using a lexical database updated from the online Khmer dictionaries and some supported dictionaries serving role of training data and complementary linguistic characteristics. Each component cluster is labelled and located by the first and last letter to identify entirety a syllable. This approach is workable and the test results achieve high accuracy, eliminate the ambiguity, contribute to solving the problem of word segmentation and applying efficiency in Khmer language processing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
