{"title":"手写体阿拉伯文本识别的基于类的上下文建模","authors":"Irfan Ahmad, G. Fink","doi":"10.1109/ICFHR.2016.0107","DOIUrl":null,"url":null,"abstract":"In this paper we will present our investigations related to contextual modeling for HMM-based handwritten Arabic text recognition. We will, first, discuss the justifications and the need for contextual modeling for handwritten Arabic text recognition. Next, we will discuss the issues related to contextual modeling for Arabic text recognition. Finally, we will present our novel class-based contextual modeling for HMM-based handwritten Arabic text recognition. Experiment results on word recognition tasks show improvements in word recognition rates when compared to using standard contextual HMMs. Moreover, the recognizers are significantly more compact as compared to the standard contextual HMM systems.","PeriodicalId":194844,"journal":{"name":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Class-Based Contextual Modeling for Handwritten Arabic Text Recognition\",\"authors\":\"Irfan Ahmad, G. Fink\",\"doi\":\"10.1109/ICFHR.2016.0107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we will present our investigations related to contextual modeling for HMM-based handwritten Arabic text recognition. We will, first, discuss the justifications and the need for contextual modeling for handwritten Arabic text recognition. Next, we will discuss the issues related to contextual modeling for Arabic text recognition. Finally, we will present our novel class-based contextual modeling for HMM-based handwritten Arabic text recognition. Experiment results on word recognition tasks show improvements in word recognition rates when compared to using standard contextual HMMs. Moreover, the recognizers are significantly more compact as compared to the standard contextual HMM systems.\",\"PeriodicalId\":194844,\"journal\":{\"name\":\"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFHR.2016.0107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFHR.2016.0107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Class-Based Contextual Modeling for Handwritten Arabic Text Recognition
In this paper we will present our investigations related to contextual modeling for HMM-based handwritten Arabic text recognition. We will, first, discuss the justifications and the need for contextual modeling for handwritten Arabic text recognition. Next, we will discuss the issues related to contextual modeling for Arabic text recognition. Finally, we will present our novel class-based contextual modeling for HMM-based handwritten Arabic text recognition. Experiment results on word recognition tasks show improvements in word recognition rates when compared to using standard contextual HMMs. Moreover, the recognizers are significantly more compact as compared to the standard contextual HMM systems.