{"title":"基于简单递归网络的口语词识别中的追溯语境效应建模","authors":"Alain Content, Pascal Sternon","doi":"10.4324/9781315789354-36","DOIUrl":null,"url":null,"abstract":"We present a new variant of a simple recurrent network to model auditory word recognition in continuous speech and address the issue of lexical segmentation. Simulations based on small word sets show that the system provides a nearoptimal solution to the opposite constraints of speed, which requires that lexical processing be immediate, and reliability, which imposes that identification decisions be postponed until unambiguous information is available. Contrary to an oftenheard statement, the simulations show that the existence of embedded words is not incompatible with the notion of continuous on-line lexical processing.","PeriodicalId":393936,"journal":{"name":"Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modelling Retroactive Context Effects in Spoken Word Recognition with a Simple Recurrent Network\",\"authors\":\"Alain Content, Pascal Sternon\",\"doi\":\"10.4324/9781315789354-36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a new variant of a simple recurrent network to model auditory word recognition in continuous speech and address the issue of lexical segmentation. Simulations based on small word sets show that the system provides a nearoptimal solution to the opposite constraints of speed, which requires that lexical processing be immediate, and reliability, which imposes that identification decisions be postponed until unambiguous information is available. Contrary to an oftenheard statement, the simulations show that the existence of embedded words is not incompatible with the notion of continuous on-line lexical processing.\",\"PeriodicalId\":393936,\"journal\":{\"name\":\"Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4324/9781315789354-36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4324/9781315789354-36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modelling Retroactive Context Effects in Spoken Word Recognition with a Simple Recurrent Network
We present a new variant of a simple recurrent network to model auditory word recognition in continuous speech and address the issue of lexical segmentation. Simulations based on small word sets show that the system provides a nearoptimal solution to the opposite constraints of speed, which requires that lexical processing be immediate, and reliability, which imposes that identification decisions be postponed until unambiguous information is available. Contrary to an oftenheard statement, the simulations show that the existence of embedded words is not incompatible with the notion of continuous on-line lexical processing.