{"title":"用最小泛化建模英语过去时直觉","authors":"Adam Albright, B. Hayes","doi":"10.3115/1118647.1118654","DOIUrl":null,"url":null,"abstract":"We describe here a supervised learning model that, given paradigms of related words, learns the morphological and phonological rules needed to derive the paradigm. The model can use its rules to make guesses about how novel forms would be inflected, and has been tested experimentally against the intuitions of human speakers.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"147","resultStr":"{\"title\":\"Modeling English Past Tense Intuitions with Minimal Generalization\",\"authors\":\"Adam Albright, B. Hayes\",\"doi\":\"10.3115/1118647.1118654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We describe here a supervised learning model that, given paradigms of related words, learns the morphological and phonological rules needed to derive the paradigm. The model can use its rules to make guesses about how novel forms would be inflected, and has been tested experimentally against the intuitions of human speakers.\",\"PeriodicalId\":186158,\"journal\":{\"name\":\"Special Interest Group on Computational Morphology and Phonology Workshop\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"147\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Special Interest Group on Computational Morphology and Phonology Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/1118647.1118654\",\"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/10.3115/1118647.1118654","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling English Past Tense Intuitions with Minimal Generalization
We describe here a supervised learning model that, given paradigms of related words, learns the morphological and phonological rules needed to derive the paradigm. The model can use its rules to make guesses about how novel forms would be inflected, and has been tested experimentally against the intuitions of human speakers.