Procedural Text Generation from an Execution Video
Atsushi Ushiku, Hayato Hashimoto, Atsushi Hashimoto, Shinsuke Mori
Abstract
In recent years, there has been a surge of interest in automatically describing images or videos in a natural language. These descriptions are useful for image/video search, etc. In this paper, we focus on procedure execution videos, in which a human makes or repairs something and propose a method for generating procedural texts from them. Since video/text pairs available are limited in size, the direct application of end-to-end deep learning is not feasible. Thus we propose to train Faster R-CNN network for object recognition and LSTM for text generation and combine them at run time. We took pairs of recipe and cooking video, generated a recipe from a video, and compared it with the original recipe. The experimental results showed that our method can produce a recipe as accurate as the state-of-the-art scene descriptions.- Anthology ID:
- I17-1033
- Volume:
- Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 326–335
- Language:
- URL:
- https://aclanthology.org/I17-1033
- DOI:
- Cite (ACL):
- Atsushi Ushiku, Hayato Hashimoto, Atsushi Hashimoto, and Shinsuke Mori. 2017. Procedural Text Generation from an Execution Video. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 326–335, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- Procedural Text Generation from an Execution Video (Ushiku et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/I17-1033.pdf