Glyph-aware Embedding of Chinese Characters

Understand

Given the advantage and recent success of English character-level and subword-unit models in several NLP tasks, we consider the equivalent modeling problem for Chinese.

• Chinese script is logographic and many Chinese logograms are composed of common substructures that provide semantic, phonetic and syntactic hints.
• In this work, we propose to explicitly incorporate the visual appearance of a character's glyph in its representation, resulting in a novel glyph-aware embedding of Chinese characters.
• Being inspired by the success of convolutional neural networks in computer vision, we use them to incorporate the spatio-structural patterns of Chinese glyphs as rendered in raw pixels.