Enyu He

Also published as: 恩宇


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2023

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融合多粒度特征的缅甸语文本图像识别方法(Burmese Language Recognition Method Fused with Multi-Granularity Features)
Enyu He (何恩宇) | Rui Chen (陈蕊) | Cunli Mao (毛存礼) | Yuxin Huang (黄于欣) | Shengxaing Gao (高盛祥) | Zhengtao Yu (余正涛)
Proceedings of the 22nd Chinese National Conference on Computational Linguistics

“缅甸语属于东南亚低资源语言,缅甸语文本图像识别对开展缅甸语机器翻译等任务具有重要意义。由于缅甸语属于典型的字符组合型语言,一个感受野内存在多个字符嵌套,现有缅甸语识别方法主要是从字符粒度进行识别,在解码时会出现某些字符未能正确识别而导致局部乱码。考虑到缅甸语存在特殊的字符组合规则,本文提出了一种融合多粒度特征的缅甸语文本图像识别方法,将较细粒度的字符粒度和较粗粒度的字符簇粒度进行序列建模,然后将两种粒度特征序列进行融合后利用解码器进行解码。实验结果表明,该方法能够有效缓解识别结果乱码的现象,并且在人工构建的数据集上相比“VGG16+BiLSTM+Transformer”的基线模型识别准确率提高2.4%,达到97.35%。 "