摘要
隐马尔可夫模型(Hidden Markov Model,HMM)在自然语言处理、语音识别、模式识别等领域都得到了广泛的应用,特别是在词性标注中起到了很好的效果。词性标注在信息处理范畴内起着重要的基础性作用,词性标注的好坏直接影响着基于标注结果的各种信息处理的准确度。基于HMM分别实现了中文词性标注与英文词性标注,并对两者进行了比较,最后分析了影响实验结果的相关因素和有待改进之处。
Hidden Markov Model（HMM） has been widely applied in natural language processing,speech recognition,and pattern recognition.Especially has a good effect in Part-of-Speech（POS） Tagging.POS Tagging plays an important fundamental role in the area of message processing.The quality of POS Tagging direct inference the accuracies of all information processing which are based on the results of tagging.This paper realizes the chinese POS tagging and the english POS tagging separately based HMM,and makes a comparison on them.At last,the paper analyzes the correlative factors which affect the results of the experiment,also analyzes the areas for improvements.
出处
《电脑开发与应用》
2011年第3期52-55,共4页
Computer Development & Applications
关键词
隐马尔可夫模型
词性标注
自然语言处理
hidden Markov model
part-of-speech tagging
natural language processing
