Structure-Aware Procedural Text Generation From an Image Sequence
Structure-Aware Procedural Text Generation From an Image Sequence
复制标题
从图像序列生成结构感知的程序文本
DOI:
10.1109/access.2020.3043452
复制
发表时间:
2020
期刊:
影响因子:
3.9
通讯作者:
Y. Yamakata and S. Mori
中科院分区:
文献类型:
--
作者:
T. Nishimura;A. Hashimoto;Y. Ushiku;H. Kameko;Y. Yamakata and S. Mori
It is an important activity for our society to create new value by combining materials. From daily cooking to manufacturing for industry, we often describe the way to do it as a procedural text. As pointed by some previous studies for natural language understanding, one important property of the procedural text is its dependency of the context, which is the merging operations of materials and can be represented by a graph or tree structure. This paper aims to investigate the impact of explicitly introducing such a structure on the vision and language task of procedural text generation from an image sequence. To this end, we propose (1) a new dataset, which extends a definition of a tree structure merging tree to a vision and language version and (2) a novel structure-aware procedural text generation model, which learns the context dependency efficiently. Experimental results show that the proposed method can boost the performance of traditional versatile methods.
DOI:
--
发表时间:
1980
期刊:
International Conference on Computational Linguistics
影响因子:
--
作者:
Yoshio Momouchi
通讯作者:
Yoshio Momouchi
DOI:
10.18653/v1/p19-1606
发表时间:
2019
期刊:
--
影响因子:
--
作者:
Khyathi Raghavi Chandu;Eric Nyberg;A. Black
通讯作者:
A. Black