文章基本信息

标题：対話穴埋め：検索・生成ベース雑談対話システムの発話制御手法
本地全文：下载
作者：薛強 ; 滝口哲也 ; 有木康雄等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2022
卷号：37
期号：3
页码：1-9
DOI：10.1527/tjsai.37-3_IDS-C
语种：Japanese
出版社：The Japanese Society for Artificial Intelligence
摘要：Generation-base dialogue system tends to produce generic response sentences. In order to improve the diversity of response sentences by the generation-base dialogue system, the response text retrieved by the retrieval-base model can be input to the generation-base model as reference response text, so that the generation-base model can generate highly diverse response sentences. However, the prior works show that the generation-base dialogue system often ignores the reference response text, resulting in the response sentences that is unrelated to the reference response text. In this work, we propose the Dialogue-Filling method, which can utilize 100% of the reference response text by masking the response sentences with a text-filling technique. We built variants of Dialogue-Filling method with DialoGPT model. Experiments on the DailyDialog Dataset demonstrate that our Dialogue-Filling method outperforms the baseline method on the dialogue generation task.
关键词：retrieval-base;generation-base;dialogue system;text-filling