JSAI2022

Presentation information

Organized Session

Organized Session » OS-12

[3H3-OS-12a] グループインタラクションとAI(1/2)

Thu. Jun 16, 2022 1:30 PM - 3:10 PM Room H (Room H)

オーガナイザ:酒造 正樹(東京電機大学)[現地]、湯浅 将英(湘南工科大学)、岡田 将吾(北陸先端科学技術大学院大学)、酒井 元気(日本大学)、近藤 一晃(京都大学)、中野 有紀子(成蹊大学)

2:30 PM - 2:50 PM

[3H3-OS-12a-04] Dialogue act classification using two multi-party discussion corpora

Shunsuke Yonemitsu1, 〇Kazutaka Shimada1 (1. Kyushu Institute of Technology)

[[Online]]

Keywords:Dialogue Act, Multi-party discussion

Dialogue act classification is an important task to summarize and analyze discussions. This paper first annotates dialogue act tags to a Japanese multi-party discussion corpus. The tag set is based on an existing multi-party conversation corpus. Then, we propose a multi-dataset learning model for dialogue act classification. In this method, the model is trained from two corpora at the same time. As another approach, we generate a model from the dataset combined from two corpora because the two corpora use the same tag set. We compare the model with multi-dataset learning. The experimental result shows the importance of the corpus size for the task.

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