“Never fry carrots without chopping” Generating Cooking Recipes from Cooking Videos Using Deep Learning Considering Previous Process
- 10.2991/ijndc.k.190710.002How to use a DOI?
- Image captioning; deep learning; cooking; recipe; Doc2Vec
Research on deep-training captioning models that modify the natural-language contents of images and moving images has produced considerable results and attracted attention in recent years. In this research, we aim to generate recipe sentences from cooking videos acquired from YouTube. We treat this as an image-captioning task and propose two methods suitable for the work. We propose a method that adds a vector of a sentence already generated in the same recipe to the input of a captioning model. Then, we compare generated and correct sentences to calculate scores. We also propose a data-processing method to improve accuracy. We use several widely used metrics to evaluate image-captioning problems. We then train the same data with the simplest encoder–decoder model, compare it with correct recipe sentences, and calculate the metrics. The results indicate that our proposed methods help increase accuracy.
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Tatsuki Fujii AU - Yuichi Sei AU - Yasuyuki Tahara AU - Ryohei Orihara AU - Akihiko Ohsuga PY - 2019 DA - 2019/07/23 TI - “Never fry carrots without chopping” Generating Cooking Recipes from Cooking Videos Using Deep Learning Considering Previous Process JO - International Journal of Networked and Distributed Computing SP - 107 EP - 112 VL - 7 IS - 3 SN - 2211-7946 UR - https://doi.org/10.2991/ijndc.k.190710.002 DO - 10.2991/ijndc.k.190710.002 ID - Fujii2019 ER -