What is an effective expression that draws laughter from human beings? In the
present paper, in order to consider this question from an academic standpoint,
we generate an image caption that draws a "laugh" by a computer. A system that
outputs funny captions based on the image caption proposed in the computer
vision field is constructed. Moreover, we also propose the Funny Score, which
flexibly gives weights according to an evaluation database. The Funny Score
more effectively brings out "laughter" to optimize a model. In addition, we
build a self-collected BoketeDB, which contains a theme (image) and funny
caption (text) posted on "Bokete", which is an image Ogiri website. In an
experiment, we use BoketeDB to verify the effectiveness of the proposed method
by comparing the results obtained using the proposed method and those obtained
using MS COCO Pre-trained CNN+LSTM, which is the baseline and idiot created by
humans. We refer to the proposed method, which uses the BoketeDB pre-trained
model, as the Neural Joking Machine (NJM).

本文介绍了一种基于计算机视觉的图像标注系统 -- Neural Joking Machine（NJM），该系统可根据主题（图像）和有趣的标题（文本）自动输出有趣的标题，并使用 Funny Score 对模型进行优化，实验结果表明，使用 NJM 的结果比使用基线（MS COCO Pre-trained CNN+LSTM）更为有效。