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MuLTReNets: Multilingual text recognition networks for simultaneous script identification and handwriting recognition | |
Chen, Zhuo1,2![]() ![]() ![]() ![]() ![]() | |
发表期刊 | Pattern Recognition
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ISSN | 0031-3203 |
2020-07-23 | |
卷号 | 108期号:107555页码:11 |
摘要 | Multilingual handwritten text recognition is often accomplished in two cascaded steps: script identification and handwriting recognition. However, this scheme is not optimal due to error accumulation. To perform simultaneous script identification and handwriting recognition, in this paper, we propose a new framework named multilingual text recognition networks (MuLTReNets). Specifically, the system has four major modules: feature extractor, script identifier, handwriting recognizer and auto-weighter. The feature extractor integrates both spatial and temporal knowledge to encode text images into features shared by the script identifier and recognizer. The script identifier predicts script category from a variable-length sequence incorporating an auto-weighter for balancing different scripts, while the handwriting recognizer adopts long-short term memory (LSTM) and Connectionist Temporal Classification (CTC) to accomplish sequence decoding. Via multi-task learning, the proposed framework can benefit both two multilingual recognition schemes: unified recognition with merged alphabet (MuLTReNetV1) and cascaded script identification-single script recognition with joint training (MuLTReNetV2). We evaluated the performance of the proposed method on handwritten text databases of five languages, which are English, French, Kannada, Urdu, and Bangla. Experimental results demonstrate that our method performs superiorly for both script identification and handwriting recognition. The accuracy of script identification reaches 99.9%. While in handwriting recognition, the proposed system not only outperforms cascade systems but also surpasses systems particularly designed for specific scripts. |
关键词 | MuLTReNets auto-weighter Separable MDLSTM multilingual handwritten text recognition multi-task learning |
DOI | 10.1016/j.patcog.2020.107555 |
关键词[WOS] | LANGUAGE IDENTIFICATION ; DATASET |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China (NSFC)[61721004] ; National Natural Science Foundation of China (NSFC)[61633021] ; National Natural Science Foundation of China (NSFC)[71621002] ; National Natural Science Foundation of China (NSFC)[61733007] ; National Natural Science Foundation of China (NSFC)[61721004] ; National Natural Science Foundation of China (NSFC)[61633021] ; National Natural Science Foundation of China (NSFC)[71621002] ; National Natural Science Foundation of China (NSFC)[61733007] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000566985000013 |
出版者 | ELSEVIER SCI LTD |
七大方向——子方向分类 | 文字识别与文档分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40625 |
专题 | 多模态人工智能系统全国重点实验室_模式分析与学习 |
通讯作者 | Chen, Zhuo |
作者单位 | 1.National Laboratory of Pattern Recognition (NLPR), Institute of Automation of Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.CAS Center for Excellence in Brain Science and Intelligence Technology |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Chen, Zhuo,Yin, Fei,Zhang, Xu-Yao,et al. MuLTReNets: Multilingual text recognition networks for simultaneous script identification and handwriting recognition[J]. Pattern Recognition,2020,108(107555):11. |
APA | Chen, Zhuo,Yin, Fei,Zhang, Xu-Yao,Yang, Qing,&Liu, Cheng-Lin.(2020).MuLTReNets: Multilingual text recognition networks for simultaneous script identification and handwriting recognition.Pattern Recognition,108(107555),11. |
MLA | Chen, Zhuo,et al."MuLTReNets: Multilingual text recognition networks for simultaneous script identification and handwriting recognition".Pattern Recognition 108.107555(2020):11. |
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