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An open dataset for the evolution of oracle bone characters: EVOBC
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The earliest extant Chinese characters originate from oracle bone inscriptions, which are closely related to other East Asian languages. These inscriptions hold immense value for anthropology and archaeology. However, deciphering oracle bone script remains a formidable challenge, with only approximately 1,600 of the over 4,500 extant characters elucidated to date. Further scholarly investigation is required to comprehensively understand this ancient writing system. Artificial Intelligence technology is a promising avenue for deciphering oracle bone characters, particularly concerning their evolution. However, one of the challenges is the lack of datasets mapping the evolution of these characters over time. In this study, we systematically collected ancient characters from authoritative texts and websites spanning six historical stages: Oracle Bone Characters - OBC (15th century B.C.), Bronze Inscriptions - BI (13th to 221 B.C.), Seal Script - SS (11th to 8th centuries B.C.), Spring and Autumn period Characters - SAC (770 to 476 B.C.), Warring States period Characters - WSC (475 B.C. to 221 B.C.), and Clerical Script - CS (221 B.C. to 220 A.D.). Subsequently, we constructed an extensive dataset, namely EVolution Oracle Bone Characters (EVOBC), consisting of 229,170 images representing 13,714 distinct character categories. We conducted validation and simulated deciphering on the constructed dataset, and the results demonstrate its high efficacy in aiding the study of oracle bone script. This openly accessible dataset aims to digitalize ancient Chinese scripts across multiple eras, facilitating the decipherment of oracle bone script by examining the evolution of glyph forms.
Forward citations
Cited by 3 Pith papers
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HCSU: A Dataset and Benchmark for Fine-Grained Historical Calligraphy Style Understanding
HCSU supplies the first large decoupled Tie/Bei calligraphy dataset with expert aesthetic labels and finds SOTA LVLMs remain knowledgeable yet unperceptive on fine-grained style.
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AlphaOracle: Oracle bone script decipherment via human-workflow-inspired deep learning
AlphaOracle integrates morphological, contextual, and philological evidence into an interpretable pipeline that reportedly assists experts in deciphering oracle bone script, reading 'Lao' as a toponym or clan name.
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MCCD: A Multi-Attribute Chinese Calligraphy Character Dataset Annotated with Script Styles, Dynasties, and Calligraphers
A 329,715-image Chinese calligraphy dataset with character, style (10), dynasty (15), and calligrapher (142) labels, plus single- and multi-task recognition benchmarks.
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