The Application of Multimodal Discourse Analysis in Urban Intercultural Communication

IF 3.1 Q1 Mathematics
Baiying Chen
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Abstract

Abstract This paper firstly analyzes the basic composition of intercultural communication ability, discusses the specific function of cultural promotion of urban tourism, and gives the promotion effect of intercultural communication on urban tourism. Secondly, the connotation of multimodal discourse analysis is given, and the technical analysis of text, audio, and visual features is carried out for the analysis of urban tourism discourse. Then, the TF-IDF algorithm is used to realize the feature extraction of tourism culture text, the MFCC algorithm is used to extract the audio features of tourism culture, and the modal classification network is used to realize the recognition of the visual features of urban tourism culture video. Finally, to verify the effectiveness of the application of multimodal discourse analysis in urban cross-cultural communication, three aspects were tested and analyzed respectively. The results show that the F1 value of the TF-IDF algorithm is 0.912, which is 17.07% higher than that of the CTF-TF-IDF algorithm. When the amount of audio recognition is 5GB, the recognition time of the MFCC audio recognition method is 10.4 s. When the weight value of the visual feature extraction network is set to 1.0, the highest visual feature extraction error rate is only 3.96%. Using multimodal discourse analysis to carry out urban tourism discourse analysis can realize more comprehensive urban tourism feature extraction, help tourists strengthen their tourism perception, and then promote the enhancement of urban cross-cultural communication ability.
多模态话语分析在城市跨文化交流中的应用
摘要本文首先分析了跨文化交际能力的基本构成,探讨了文化促进城市旅游的具体功能,给出了跨文化交际对城市旅游的促进作用。其次,给出了多模态语篇分析的内涵,并对城市旅游语篇进行了文本特征、音频特征和视觉特征的技术分析。然后,利用TF-IDF算法实现旅游文化文本的特征提取,利用MFCC算法提取旅游文化音频特征,利用模态分类网络实现城市旅游文化视频视觉特征的识别。最后,为了验证多模态语篇分析在城市跨文化交际中应用的有效性,我们分别从三个方面进行了测试和分析。结果表明,TF-IDF算法的F1值为0.912,比CTF-TF-IDF算法的F1值高17.07%。当音频识别量为5GB时,MFCC音频识别方法的识别时间为10.4 s。当视觉特征提取网络的权值设置为1.0时,视觉特征提取的最高错误率仅为3.96%。利用多模态语篇分析开展城市旅游语篇分析,可以实现更全面的城市旅游特征提取,帮助游客增强旅游感知,进而促进城市跨文化交际能力的提升。
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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