著者

小池 隆斗 萩原 将文

出版者

日本感性工学会

雑誌

日本感性工学会論文誌 (ISSN:18845258)

巻号頁・発行日

vol.21, no.1, pp.49-55, 2022 (Released:2022-02-28)

参考文献数

23

被引用文献数

1

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The generation of attractive sentences for consumers is an important issue. In this paper, we propose a new method to generate title sentences that are more popular on YouTube, which is gaining large popularity in recent years. In the proposed method, the automatic generation of titles is regarded as a sentence style transfer task; The title sentence generated by the video creator is transformed into a more attractive one. Specifically, first, the latent variable is obtained by the back translation method. In the back translation method, it translates the original title into another language and retranslates it into Japanese. Then, style transfer is performed based on this latent variable to generate a more attractive title sentence. In addition, transfer learning is employed to address the problem of scarce training data. Subjective evaluation experiments have been conducted to show the effectiveness of the proposed method.