Evaluation of Neural Network Language Models in Handwritten Chinese Text Recognition

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	Evaluation of Neural Network Language Models in Handwritten Chinese Text Recognition
	Wu YC(吴一超); Yin F(殷飞); Liu CL(刘成林)
	2015
会议日期	2015-8-23
会议地点	法国南锡
英文摘要	Handwritten Chinese text recognition based on over-segmentation and path search integrating contexts has been demonstrated successful, where language models play an important role. Recently, neural network language models (NNLMs) have shown superiority to back-off N-gram language models (BLMs) in handwriting recognition, but have not been studied in Chinese text recognition system. This paper investigates the effects of NNLMs in handwritten Chinese text recognition and compares the performance with BLMs. We trained characterlevel language models in 3-, 4- and 5- gram on large scale corpora and applied them in text line recognition system. Experimental results on the CASIA-HWDB database show that NNLM and BLM of the same order perform comparably, and the hybrid model by interpolating NNLM and BLM improves the recognition performance significantly.
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/19797]
专题	自动化研究所_模式识别国家重点实验室_模式分析与学习团队
作者单位	Institute of Institute of Automation,Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Wu YC,Yin F,Liu CL. Evaluation of Neural Network Language Models in Handwritten Chinese Text Recognition[C]. 见:. 法国南锡. 2015-8-23.