口语对话中的语句主题分析

本文研究如何根据浅层的语义分析确定自然口语对话中的语句主题。首先将对话中的语句主题定义为说话者所关注的显著语义实体,并讨论了这样的语句主题所具有的两个特点(即话语性和连续性) 以及语句主题跟(扩展) 句子类型的关系(因而也介绍了句子类型及其扩展和扩展句子类型的识别) 。然后根据这些建立了语句主题分析算法,并在实际的对话语料中进行分析。实验结果表明,语句主题的分析正确率可达到6111～8716 % ,取决于不同的扩展句子类型和不同的正确率定义。

Utterance Topic Identification in Spoken Dialogues

This paper investigates how to identify utterance topics in spontaneous spoken dialogues based on some shallow semantic analysis. First the topic of an utterance is defined as the salient semantic entity its speaker focuses hisPher attention on. Then we discuss two features of such a topic (i. e. , topic as discourse construct and topic continuity) and the relationship between utterance topic and (extended) sentence type. According to these an algorithm is established to identify utterance topic and evaluated in a spoken dialogue corpus. The results achieve an accuracy of 6111～8716 % , depending on different sources of extended sentence type and different accuracy definitions.