Sherif Zeyada, M. Eladawy, Manal A. Ismail, H. Keshk
{"title":"A Proposed System for the Identification of Modem Arabic Poetry Meters (IMAP)","authors":"Sherif Zeyada, M. Eladawy, Manal A. Ismail, H. Keshk","doi":"10.1109/ICCES51560.2020.9334614","DOIUrl":null,"url":null,"abstract":"Recognizing the prosody or arud of modern Arabic poems in an automatic way is a big challenge. One of these challenges is the rare work in this field. We found very few publications on recognizing the classical poems arud, but, as far as we know we did not find any publication on applying machine learning techniques to recognize the arud for modern poems where there are no definite numbers of feet for each verse, no fixed rhyme, and meters are mixed. In this paper, we introduce a new system using Artificial intelligence called “IMAP” to identify and recognize the arud for modern Arabic poems. Tafhela (Foot) is a group of syllables that form a prosodic unit regardless of word boundaries. The accuracy of our proposed algorithm was 99%.","PeriodicalId":247183,"journal":{"name":"2020 15th International Conference on Computer Engineering and Systems (ICCES)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 15th International Conference on Computer Engineering and Systems (ICCES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCES51560.2020.9334614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Recognizing the prosody or arud of modern Arabic poems in an automatic way is a big challenge. One of these challenges is the rare work in this field. We found very few publications on recognizing the classical poems arud, but, as far as we know we did not find any publication on applying machine learning techniques to recognize the arud for modern poems where there are no definite numbers of feet for each verse, no fixed rhyme, and meters are mixed. In this paper, we introduce a new system using Artificial intelligence called “IMAP” to identify and recognize the arud for modern Arabic poems. Tafhela (Foot) is a group of syllables that form a prosodic unit regardless of word boundaries. The accuracy of our proposed algorithm was 99%.