Unsupervised Approach for Dialogue Act Classification

被引：0

作者：

Ohtake, Kiyonori ^{[1
]}

机构：

[1] Natl Inst Informat & Commun Technol, Adv Telecommun Res Inst Int, Keihanna Sci City 6190288, Japan

来源：

PACLIC 22: PROCEEDINGS OF THE 22ND PACIFIC ASIA CONFERENCE ON LANGUAGE, INFORMATION AND COMPUTATION | 2008年

关键词：

Unsupervised; Dialogue Act; Paraphrasing; Latent Variable Model;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an unsupervised approach for dialogue act (DA) classification. We used a latent variable model to compress the dimensions of the feature vector. We introduced a paraphraser to reduce the variety of expressions and to solve the pragmatic problem for DA classification. The paraphraser seemed to work well on some DA classifications in the unsupervised approach. The results obtained by the unsupervised approach were compared with the manually annotated labels. A preliminary experiment for semi-supervised tagging was also carried out, and we discuss these results.

引用

页码：445 / 451

页数：7

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