{"title":"生成电子:一个虚拟制作人和虚拟DJ","authors":"Arne Eigenfeldt","doi":"10.1145/2466627.2481234","DOIUrl":null,"url":null,"abstract":"We present a virtual Electronic Dance Music (EDM) producer that generates stylistically accurate Breakbeat music. GESMI, the Generative Electronica Statistical Modeling Instrument, uses a corpus of human-analysed Breakbeat tracks dating from 1994--2010: the system learns relevant musical information in order to produce a wide variety of music within the genre using knowledge culled from the transcriptions.","PeriodicalId":333903,"journal":{"name":"Proceedings of the 9th ACM Conference on Creativity & Cognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Generating electronica: a virtual producer and virtual DJ\",\"authors\":\"Arne Eigenfeldt\",\"doi\":\"10.1145/2466627.2481234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a virtual Electronic Dance Music (EDM) producer that generates stylistically accurate Breakbeat music. GESMI, the Generative Electronica Statistical Modeling Instrument, uses a corpus of human-analysed Breakbeat tracks dating from 1994--2010: the system learns relevant musical information in order to produce a wide variety of music within the genre using knowledge culled from the transcriptions.\",\"PeriodicalId\":333903,\"journal\":{\"name\":\"Proceedings of the 9th ACM Conference on Creativity & Cognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 9th ACM Conference on Creativity & Cognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2466627.2481234\",\"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 9th ACM Conference on Creativity & Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2466627.2481234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generating electronica: a virtual producer and virtual DJ
We present a virtual Electronic Dance Music (EDM) producer that generates stylistically accurate Breakbeat music. GESMI, the Generative Electronica Statistical Modeling Instrument, uses a corpus of human-analysed Breakbeat tracks dating from 1994--2010: the system learns relevant musical information in order to produce a wide variety of music within the genre using knowledge culled from the transcriptions.
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