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Automatic captioning tasks that describe the content of images and moving images in natural language have important applications in areas such as search technology. In addition, captioning can assist with understanding content. Understanding of content can be deepened in a short time by reading captions. Among captioning models that use deep training, the encoder–decoder [1] model has generated considerable results and attracted attention, but many existing studies only consider the consistency of contiguous scenes over short periods. Considering the consistency of video segments as a matter of captioning has high importance. Generating cooking recipe sentences from cooking videos can be considered a captioning problem by treating recipes as captions. In addition, because the cooking video is constituted as a set of fragmentary tasks, a model that considers the consistency of the whole video is considered to be effective.

“Never fry carrots without chopping” Generating Cooking Recipes from Cooking Videos Using Deep Learning Considering Previous Process