Multimodal Translation Model of Chinese Culture Based on SPSS Cluster Analysis
- DOI
- 10.2991/978-94-6463-242-2_63How to use a DOI?
- Keywords
- SPSS Clustering; Chinese Culture; Multimodal Analysis; Translation Model
- Abstract
The dissemination of national culture is a form of expression in global communication. In the early years, international media often communicated specific cultural values to the world through “soft cultural” content such as American movies and Japanese cartoons, but the one-way communication is gradually being changed. Currently, China’s soft power is increasing, and Chinese culture is also spreading to the world. In cultural research, SPSS (Statistical Product and Service Solutions) is a very important tool. It can be used for the transmission of information such as text, sound, and video data. This article aims to propose an effective method for accurately translating Chinese culture into English through the study of a multimodal translation model of Chinese culture. This article adopts methods such as case analysis and experimental research to study the multimodal translation model of Chinese culture. The results indicate that by using the multimodal translation model for materials of Chinese culture, the accuracy is relatively high, about 98%, and the error rate is relatively low.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ruihua Nai AU - Hanita Hassan PY - 2023 DA - 2023/09/22 TI - Multimodal Translation Model of Chinese Culture Based on SPSS Cluster Analysis BT - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023) PB - Atlantis Press SP - 509 EP - 518 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-242-2_63 DO - 10.2991/978-94-6463-242-2_63 ID - Nai2023 ER -