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Study on the evolution of Chinese characters based on few-shot learning: From oracle bone inscriptions to regular
Mengru Wang1,2, Yu Cai1, Li Gao3
1Key Laboratory for Special Functional Materials of Ministry of Education, and School of Materials Science and Engineering, Henan University, Kaifeng, China.
Plos One
|August 19, 2022
Summary
This study introduces a Few-shot learning (FSL) approach using Siamese networks to decipher ancient Chinese oracle bone inscriptions (OBIs). The VGG16-Siamese network achieved 83.3% F1 score, offering a new method for OBI decipherment.
Area of Science:
- Computational Linguistics
- Artificial Intelligence
- Archaeology
Background:
- Oracle bone inscriptions (OBIs) are ancient Chinese scripts from the Shang Dynasty, with less than half currently deciphered.
- Deciphering remaining OBIs relies on historical analysis and faces significant challenges.
Purpose of the Study:
- To systematically analyze the evolution of oracle characters using Few-shot learning (FSL).
- To develop a computational method to aid in the decipherment of OBIs.
Main Methods:
- A dataset of Chinese characters across five evolutionary periods (OBIs, bronze, seal, official, regular script) was created.
- Siamese networks with VGG16, ResNet, and AlexNet backbones were employed for character evolution analysis.
- Performance comparison of different network architectures was conducted.
Main Results:
- The VGG16-Siamese network combination achieved the highest F1 score of 83.3% and recognition accuracy of 82.67%.
- The study evaluated the typical structural performance of characters across different evolutionary periods.
- The optimized Siamese network demonstrated feasibility for studying OBI evolution.
Conclusions:
- The developed Siamese network approach provides a novel computational tool for OBI decipherment.
- This method offers a new avenue to overcome the current bottleneck in understanding ancient Chinese scripts.
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