摘要
语言分析和知识库管理是口语理解与对话系统的两个重要组成部分 ,作者在这两方面提出了一些新的方法。一是提出并实现了词类概率模型 ,它具有较高的性能和较低的时间复杂度 ,是基于句法规则的语义分析和语言理解的基础。此外还提出了与数据无关的多叉树层次结构模型的知识表示方法 ,它具有很强的表达能力并易于扩展。在此基础上 ,实现了一个用以提供清华大学地理、办公、商业及其它一些相关信息检索、基于文本的口语对话系统 Easy Nav。实验表明 。
Language analysis (parsing) and knowledge library management are the most significant parts of a spoken language understanding and dialogue system. Some new approaches to language analysis and knowledge library management are presented. The proposed Word Class Stochastic Model (WCSM) is the basis for syntax rule based semantic parsing and spoken language understanding which has better performance. The data independent multi branch tree hierarchical structure is proposed for the knowledge representation, because it has strong expressing ability and can be easily expanded. EasyNav, a text based dialogue system based on these concepts, is designed and implemented to provide users with Tsinghua University campus navigation information. Experiments on EasyNav give satisfactory performances with these two models.
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2001年第1期69-72,共4页
Journal of Tsinghua University(Science and Technology)
关键词
口语对话系统
自然语言理解
词类概率模型
知识表示
人机对话
spoken language dialogue system
natural language understanding
word class stochastic model
knowledge representation
