研究了信息类自然口语对话中的交互模式及其自动分析.首先,基于话语分析中的Birmingham学派关于交互模式的工作和Halliday关于言语功能的分析,提出使用语句组采刻画交互模式,并建立原则性分类体系:然后,对语料中的交互模式进行标注分析;随后.才艮据影响语句组结构的主要因素建立交互模式分析算法,并在语料中进行实验.实验结果表明,语句组的整体分析正确率可达到55.4%~84.2%——取决于不同来源的扩展句子类型和语句主题的分析结果.
In this paper, the interaction patterns and their automatic analysis in spontaneous spoken information-seeking dialogues are studied. First, based on previous work from discourse analysis (i,e., exchange as basic interaction unit in Birmingham School) and Sytemic Functional Grammar (i.e., Halliday's speech function), a principled scheme is proposed to model interaction patterns with utterance groups. Then a dialogue corpus is annotated with this scheme and further analyzed. Some main factors affecting the structure of utterance group are distinguished. Based on these, an algorithm is established to analyze utterance groups and is evaluated in the corpus. The results achieve a correct rate of 55.4%~84.2% for overall utterance tags, depending on the different recognition performances of the extended sentence type and utterance topic.