Dialogue Act Classification In Human-to-Human Tutorial Dialogues

被引：6

作者：

Rus, Vasile ^{[1
]}

Maharjan, Nabin ^{[1
]}

Banjade, Rajendra ^{[1
]}

机构：

[1] Univ Memphis, Memphis, TN 38152 USA

来源：

INNOVATIONS IN SMART LEARNING | 2017年

关键词：

macro-adaptation; intelligent tutoring systems; assessment;

D O I：

10.1007/978-981-10-2419-1_25

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We present in this paper preliminary results with dialogue act classification in human-to-human tutorial dialogues. Dialogue acts are ways to characterize the actions of tutors and students based on the language-as-action theory. This work serves our larger goal of identifying patterns of tutors' actions, in the form of dialogue acts, that relate to learning. The preliminary results we obtained for dialogue act classification using a machine learning approach are promising.

引用

页码：183 / 186

页数：4

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