Wenting Zhang
Papers
1
Total Citations
2
H-Index
1
About
Wenting Zhang is a researcher whose work bridges artificial intelligence, natural language processing, and educational technology. Her most-cited paper, "Convolutional neural network for substantiation of children's books, intelligent interactive communication and application analysis of voice question answering" (2023), has garnered 2 citations, reflecting an emerging focus on leveraging deep learning to enhance interactive learning experiences. Zhang’s contributions center on applying convolutional neural networks to validate and enrich children's literature, while exploring voice-based question-answering systems for more intuitive human-computer interaction. This work demonstrates her interest in making AI accessible and beneficial for young learners, combining technical rigor with practical applications in education. Though early in her career, Zhang’s research signals a commitment to developing intelligent systems that foster engagement and comprehension through natural communication. Her efforts highlight the potential of AI to transform how children interact with digital content, paving the way for more adaptive and responsive educational tools. As her citation count grows, Zhang’s interdisciplinary approach—merging computer vision, speech processing, and pedagogy—positions her as a promising voice in the field of AI-driven learning technologies.
Research Focus
Key Achievements
Top Papers
- 1