基于TBL算法的汉语韵律词预测  

Predicting chinese prosodic word based on transformation-based error-driven learning

作　　者：陈龙[1] 杨鸿武[1] 蔡莲红[2] 

机构地区：[1]西北师范大学物理与电子工程学院,甘肃兰州730070 [2]清华大学计算机科学与技术系,北京100084

出　　处：《西北师范大学学报（自然科学版）》2008年第1期47-51,共5页Journal of Northwest Normal University(Natural Science)

基　　金：西北师范大学科研骨干培育项目(NWNU-KJCXGC-03-42)

摘　　要：提出了一种新的汉语韵律词预测方法.利用标注过的语料,分析了语法词与韵律词之间的关系,发现24%的韵律词由不同语法词组合而成,语法词的词长是确定韵律词边界的主要特征.基于以上分析,实现了一种基于错误驱动的规则学习算法(TBL)的韵律词预测方法.实验结果表明,所提出的方法在测试集上能够达到97.5%的预测精度.A novel approach for predicting chinese prosodic word is introduced. By analyzing a manual tagged corpus, the relationship between lexical word and prosodic word are found. The analysis results show that 24% prosodic words consist of two or more lexical words, and the length of lexical word is a most important feature for predicting prosodic words. A transformation-based error-driven learning algorithm is proposed to predicting prosodic word with lexical features. Experiments demonstrat that the proposed approach outperform other methods with over 97.5% predicting precision.

关 键 词：韵律词 语法词 TBL算法 文语转换 

分 类 号：TN912.3[电子电信—通信与信息系统]