Back to the Origin: An Intelligent System for Learning Chinese Characters

Abstract

Learning Chinese characters is a challenging task for both native and foreign beginners. One major reason is that most Chinese characters in writing are distinct from each other and lack of directly phonetic clues. Fortunately, many Chinese characters’ original forms have iconicity that indicates their meanings. By leveraging on these characteristics and the latest computer vision (CV) techniques, we design and build an intelligent system that could automatically retrieve the iconic and original forms of Chinese characters. Furthermore, the system could provide learners with different styles of the character in a chronological order to bridge the original form and the most commonly used one. Specifically, we adopt the SE-Resnet-50 classification model for both character recognition and style recognition tasks, and design a dedicated retrieval mechanism to properly select the representative characters in different styles for learners. A specific user interface is designed for beginners to upload, recognize, remember, and understand the Chinese characters.