Abstract
The Oracle Bone Characters are the earliest known ancient Chinese characters and are an important record of the civilization of ancient China.The interpretation of the Oracle Bone Characters is challenging and requires professional knowledge from ancient Chinese language experts. Although some works have utilized deep learning to perform image detection and recognition using the Oracle Bone Characters, these methods have proven difficult to use for the interpretation of uninterpreted Oracle Bone Character images. Inspired by the prior knowledge that there exists a relation between glyphs from Oracle Bone Character images and images of modern Chinese characters, we proposed a method of image translation from Oracle Bone Characters to modern Chinese characters based on the use of a generative adversarial network to capture the implicit relationship between glyphs from Oracle Bone Characters and modern Chinese characters. The image translation process between Oracle Bone Characters and the modern Chinese characters forms a symmetrical structure, comprising an encoder and decoder. To our knowledge, our symmetrical image translation method is the first of its kind used for the task of interpreting Oracle Bone Characters. Our experiments indicated that our image translation method can provide glyph information to aid in the interpretation of Oracle Bone Characters.
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