Unsupervised language model adaptation for handwritten Chinese text recognition
Wang, Qiu-Feng; Yin, Fei; Liu, Cheng-Lin
发表期刊PATTERN RECOGNITION
2014-03-01
卷号47期号:3页码:1202-1216
文章类型Article
摘要

This paper presents an effective approach for unsupervised language model adaptation (LMA) using multiple models in offline recognition of unconstrained handwritten Chinese texts. The domain of the document to recognize is variable and usually unknown a priori, so we use a two-pass recognition strategy with a pre-defined multi-domain language model set. We propose three methods to dynamically generate an adaptive language model to match the text output by first-pass recognition: model selection, model combination and model reconstruction. In model selection, we use the language model with minimum perplexity on the first-pass recognized text. By model combination, we learn the combination weights via minimizing the sum of squared error with both L2-norm and L1-norm regularization. For model reconstruction, we use a group of orthogonal bases to reconstruct a language model with the coefficients learned to match the document to recognize. Moreover, we reduce the storage size of multiple language models using two compression methods of split vector quantization (SVQ) and principal component analysis (PCA). Comprehensive experiments on two public Chinese handwriting databases CASIA-HWDB and HIT-MW show that the proposed unsupervised LMA approach improves the recognition performance impressively, particularly for ancient domain documents with the recognition accuracy improved by 7 percent. Meanwhile, the combination of the two compression methods largely reduces the storage size of language models with little loss of recognition accuracy. (C) 2013 Elsevier Ltd. All rights reserved.

关键词Character String Recognition Chinese Handwriting Recognition Unsupervised Language Model Adaptation Language Model Compression
WOS标题词Science & Technology ; Technology
关键词[WOS]CHARACTER-RECOGNITION ; OFFLINE RECOGNITION
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000329888800026
引用统计
被引频次:10[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/3088
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
作者单位Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China
第一作者单位模式识别国家重点实验室
推荐引用方式
GB/T 7714
Wang, Qiu-Feng,Yin, Fei,Liu, Cheng-Lin. Unsupervised language model adaptation for handwritten Chinese text recognition[J]. PATTERN RECOGNITION,2014,47(3):1202-1216.
APA Wang, Qiu-Feng,Yin, Fei,&Liu, Cheng-Lin.(2014).Unsupervised language model adaptation for handwritten Chinese text recognition.PATTERN RECOGNITION,47(3),1202-1216.
MLA Wang, Qiu-Feng,et al."Unsupervised language model adaptation for handwritten Chinese text recognition".PATTERN RECOGNITION 47.3(2014):1202-1216.
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