{"title":"形态切分可以改善音节化","authors":"Garrett Nicolai, Lei Yao, Grzegorz Kondrak","doi":"10.18653/v1/W16-2016","DOIUrl":null,"url":null,"abstract":"Syllabification is sometimes influenced by morphological boundaries. We show that incorporating morphological information can improve the accuracy of orthographic syllabification in English and German. Surprisingly, unsupervised segmenters, such as Morfessor, can be more useful for this purpose than the supervised ones.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Morphological Segmentation Can Improve Syllabification\",\"authors\":\"Garrett Nicolai, Lei Yao, Grzegorz Kondrak\",\"doi\":\"10.18653/v1/W16-2016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Syllabification is sometimes influenced by morphological boundaries. We show that incorporating morphological information can improve the accuracy of orthographic syllabification in English and German. Surprisingly, unsupervised segmenters, such as Morfessor, can be more useful for this purpose than the supervised ones.\",\"PeriodicalId\":186158,\"journal\":{\"name\":\"Special Interest Group on Computational Morphology and Phonology Workshop\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Special Interest Group on Computational Morphology and Phonology Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/W16-2016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Special Interest Group on Computational Morphology and Phonology Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W16-2016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Morphological Segmentation Can Improve Syllabification
Syllabification is sometimes influenced by morphological boundaries. We show that incorporating morphological information can improve the accuracy of orthographic syllabification in English and German. Surprisingly, unsupervised segmenters, such as Morfessor, can be more useful for this purpose than the supervised ones.
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