摘要
人工智能技术的发展给古文字研究带来深刻的变革。在神经网络等算法的助力下,古文字资料缀合、校重、字形识别、知识图谱与多模态数据集建设等领域都取得了较大进展。古文字学界通过跨学科项目、交叉实验室等形式寻求与人工智能工作者的合作,形成了协同攻关的学术生态。然而,人工智能辅助古文字学研究仍面临着数据量不足、数据标注困难、思路局限等问题,导致其与古文字考释的实际需求存在一定距离。本文梳理了当前人工智能辅助古文字学研究的成果、学术生态与挑战,并展望了该领域未来的发展趋势。
The development of artificial intelligence(AI)is profoundly transforming the field of paleography.Powered by algorithms such as deep neural networks,significant progress has been achieved in areas including the reconstruction and collation of ancient script materials,character recognition,and the construction of knowledge graphs and multimodal datasets.Scholars in paleography have increasingly sought collaboration with AI researchers through interdisciplinary projects and cross-disciplinary laboratories,forming an academic ecosystem characterized by collaborative research.However,AI-assisted paleographic studies still face challenges such as data scarcity,difficulties in annotation,and methodological limitations,which create a gap between current technological capabilities and the practical demands of paleographic interpretation.This paper reviews recent achievements,the emerging academic ecosystem,and existing challenges in AI-assisted paleography,and off ers perspectives on its future development.
作者
张翘楚
程少轩
ZHANG Qiaochu;CHENG Shaoxuan
出处
《汉字汉语研究》
2025年第4期3-11,125,共10页
The Study Of Chinese Characters And Language
基金
2025年江苏省高等教育教改研究课题“数智赋能古文字强基:构建文理交叉融合育人新生态”(2025JGYB324)的阶段性成果。
