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JTCLT Abstract

Volume 15 Number 1, 2024
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Wang, T. (2024). The Design and Application of a Chinese Audio-Visual Corpus Based on AI Technology. Journal of Technology and Chinese Language Teaching, 15(1), 70-81.
[王涛. (2024). 基于AI技术的CVC中文视听语料库设计与应用. 科技与中文教学 (Journal of Technology and Chinese Language Teaching), 15(1), 70-81.]

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Cultivating an AI-powered language teaching ecosystem has introduced a new model of human-computer collaboration. Many learners are acquiring information and knowledge in a manner that is more contextualized and intelligent. Many educators are adaptive to explore a variety of media resources and AI technologies to guide learners in developing capabilities in problems resolving and knowledge integration. This article describes the design and application of a Chinese Audio-Visual Corpus (CVC) that collects visual language materials from native Chinese speakers in their daily lives to associate textbook content, ontological knowledge, and video materials data in order to provide learners with context-aware teaching resource applications. This AI-based audio-visual corpus offers resourceful and intelligent language teaching methods with the priority of video content retrieval. In addition to serving language teaching, the annotated results from this audio-visual corpus will aid in the training of language models in the interdisciplinary field of Natural Language Processing (NLP) and Computer Vision (CV). It meets the demand for multimodal big data in artificial intelligence for applications such as multimodal discourse analysis, speech act recognition, and sentiment analysis, thereby contributing to the future development of the field of artificial intelligence.


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