Construction and Application of English-Chinese Multimodal Emotional Corpus Based on Artificial Intelligence.
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| Title: | Construction and Application of English-Chinese Multimodal Emotional Corpus Based on Artificial Intelligence. |
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| Authors: | Zhou, Wei1 (AUTHOR) zhouwei@hrbeu.edu.cn, Gao, Bei2 (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Feb2025, Vol. 41 Issue 3, p1782-1793. 12p. |
| Subjects: | Language awareness, Modern languages, Native language, Information technology, Chinese language |
| Abstract: | Multimodal corpus is a new type of multimedia teaching aid tool that was born and widely used in the current social development and educational reform process. It is mainly based on computer technology and network technology, and uses various multimedia materials as corpus to establish a more comprehensive English database. Corpus is increasingly used in English-Chinese multimodal teaching. Combining the content of the corpus with modern information technology will help to better understand the meaning, usage and collocation of English and Chinese multimodality, and then improve the initiative of autonomous learning. Furthermore, English-Chinese multimodality is a fixed or semi-fixed programmed language, which can be directly extracted from memory according to the context during use, which can effectively improve learners' writing efficiency and overcome the negative impact of native language transfer. Facing the task of sentiment analysis, this article has taken the text semantic representation technology based on representation learning as the main method, and carries out a series of researches from the definition of implicit emotion, the characteristics of language expression and the recognition method. Finally, in the language system of modern Chinese, it is found that there are many sentence patterns that are very similar to the middle verb structure in language expression, but the efficiency is still improved by 3.6%. Compared with traditional methods, the English-Chinese multimodal sentiment corpus method based on artificial intelligence can better reflect the application value of language, which also helps to feel the real context, change the way of thinking, and make the way of thinking more suitable for the language awareness of native speakers, thereby improving the vividness of language expression. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Multimodal corpus is a new type of multimedia teaching aid tool that was born and widely used in the current social development and educational reform process. It is mainly based on computer technology and network technology, and uses various multimedia materials as corpus to establish a more comprehensive English database. Corpus is increasingly used in English-Chinese multimodal teaching. Combining the content of the corpus with modern information technology will help to better understand the meaning, usage and collocation of English and Chinese multimodality, and then improve the initiative of autonomous learning. Furthermore, English-Chinese multimodality is a fixed or semi-fixed programmed language, which can be directly extracted from memory according to the context during use, which can effectively improve learners' writing efficiency and overcome the negative impact of native language transfer. Facing the task of sentiment analysis, this article has taken the text semantic representation technology based on representation learning as the main method, and carries out a series of researches from the definition of implicit emotion, the characteristics of language expression and the recognition method. Finally, in the language system of modern Chinese, it is found that there are many sentence patterns that are very similar to the middle verb structure in language expression, but the efficiency is still improved by 3.6%. Compared with traditional methods, the English-Chinese multimodal sentiment corpus method based on artificial intelligence can better reflect the application value of language, which also helps to feel the real context, change the way of thinking, and make the way of thinking more suitable for the language awareness of native speakers, thereby improving the vividness of language expression. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10447318 |
| DOI: | 10.1080/10447318.2023.2169526 |
