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Automatic Generation of Funny-Dialog Based on Cuisine Recipes

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Advances in Networked-based Information Systems (NBiS 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 183))

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Abstract

Laughter is generally important in our daily lives. Then, we have studied the automatic generation of funny dialogue with is called “Manzai” to provide daily laughter for people. In Japan, the Manzai is one of the most popular funny content. Generally, the themes of Manzai are familiar to people. The reason is that users need to understand and empathize with them. Therefore, we propose a method for automatically generating a script for Manzai based on a recipe that anyone can understand. Specifically, our proposed method generates Manzai scripts focusing on a recipe’s ingredients, cooking tools, and cooking actions.

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Notes

  1. 1.

    https://www.helpguide.org/articles/mental-helth/laughter-is-the-best-medicine.htmref.osaka.lg.jp/attach/4002/00029624/waraisasshi.pdf.

  2. 2.

    https://openai.com/blog/chatgpt.

References

  1. Aoki, S., Umetani, T., Kitamura, T., Nadamoto, A.: Generating Manzai-scenario using entity mistake. In: Barolli, L., Enokido, T., Takizawa, M. (eds.) NBiS 2017. LNDECT, vol. 7, pp. 1007–1017. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-65521-5_92

    Chapter  Google Scholar 

  2. Elsweiler, D., Trattner, C., Harvey, M.: Exploiting food choice biases for healthier recipe recommendation. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017, pp. 575–584. Association for Computing Machinery, New York (2017). https://doi.org/10.1145/3077136.3080826. ISBN 9781450350228

  3. Go, K., Onishi, T., Ogushi, A., Miyata, A.: Conversational agents replying with a Manzai-style joke. In: Proceedings of the 33rd Australian Conference on Human-Computer Interaction, OzCHI 2021, pp. 221–230. Association for Computing Machinery, New York (2022). https://doi.org/10.1145/3520495.3520517. ISBN 9781450395984

  4. Hayashi, K., Kanda, T., Miyashita, T., Ishiguro, H., Hagita, N.: Robot Manzai - robots’ conversation as a passive social medium. In: 5th IEEE-RAS International Conference on Humanoid Robots (2005)

    Google Scholar 

  5. Hidetsugu, N., Toshiyuki, T., Yoko, D., Tsujita, M., Sumiya, K.: Construction of a cooking ontology from cooking recipes and patents. In: Construction of a Cooking Ontology from Cooking Recipes and Patents, pp. 507–516 (2014)

    Google Scholar 

  6. Lien, Y.-C., Zamani, H., Bruce Croft, W.: Recipe retrieval with visual query of ingredients. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, pp. 1565–1568. Association for Computing Machinery, New York (2020). https://doi.org/10.1145/3397271.3401244. ISBN 9781450380164

  7. Masahiro, K., Minami, S., Chizuru, H., Keisuke, M., Varshney, L.R., Yoshiki, I.: A neural network system for transformation of regional cuisine style. In: A Neural Network System for Transformation of Regional Cuisine Style, vol. 5 (2017)

    Google Scholar 

  8. Ohashi, M., et al.: A Sense and Word of “Delicious” and a Generation of Food Texture. BMTF Publisher (2010)

    Google Scholar 

  9. Ryo, M., Tomohiro, U., Tatsuya, K., Akiyo, N.: Automatic generation of Japanese traditional funny scenario from web content based on web intelligence. In: Proceedings of the 17th International Conference on Information Integration Web-based Applications & Services, pp. 173–165 (2015)

    Google Scholar 

  10. Vilk, J., Fitter, N.T.: Comedians in cafes getting data: evaluating timing and adaptivity in real-world robot comedy performance. In: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2020, pp. 223–231. Association for Computing Machinery, New York (2020). https://doi.org/10.1145/3319502.3374780. ISBN 9781450367462

  11. Weber, K., Ritschel, H., Lingenfelser, F., André, E.: Real-time adaptation of a robotic joke teller based on human social signals. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2018, pp. 2259–2261 (2018)

    Google Scholar 

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Acknowledgement

This work was partially supported by the Research Institute of Konan University and the Premier project of Konan University.

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Correspondence to Amon Shimozaki .

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Shimozaki, A., Yamamoto, J., Nadamoto, A. (2023). Automatic Generation of Funny-Dialog Based on Cuisine Recipes. In: Barolli, L. (eds) Advances in Networked-based Information Systems. NBiS 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-031-40978-3_24

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