{"title":"把你的管乐器变成一个音乐控制器:通过分类反射白噪声的实时指法估计","authors":"Naoyuki Terashita, Kyoichi Sugahara, Yosuke Terashita","doi":"10.1145/3411763.3451719","DOIUrl":null,"url":null,"abstract":"We propose a novel fingering estimation method that allows a player to use any wind instrument as a music controller by attaching a single microphone and loudspeaker-embedded mouthpiece. The loudspeaker plays white noise continuously while the fingerings are estimated in real-time based on the sound pressure recorded at the end of the instrument. Our method addresses a major problem of conventional music controllers: differences in the tactile feel of keys compared to the player’s own instrument. We demonstrated that the proposed method accurately estimated fingerings on a saxophone with promising performance (a 1.05 % misclassification rate), satisfying the low-latency feedback required in the context of musical performance.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":"159 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Turning Your Wind Instrument into a Music Controller: Real-time Fingering Estimation by Classifying Reflected White Noise\",\"authors\":\"Naoyuki Terashita, Kyoichi Sugahara, Yosuke Terashita\",\"doi\":\"10.1145/3411763.3451719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel fingering estimation method that allows a player to use any wind instrument as a music controller by attaching a single microphone and loudspeaker-embedded mouthpiece. The loudspeaker plays white noise continuously while the fingerings are estimated in real-time based on the sound pressure recorded at the end of the instrument. Our method addresses a major problem of conventional music controllers: differences in the tactile feel of keys compared to the player’s own instrument. We demonstrated that the proposed method accurately estimated fingerings on a saxophone with promising performance (a 1.05 % misclassification rate), satisfying the low-latency feedback required in the context of musical performance.\",\"PeriodicalId\":265192,\"journal\":{\"name\":\"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems\",\"volume\":\"159 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3411763.3451719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3411763.3451719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Turning Your Wind Instrument into a Music Controller: Real-time Fingering Estimation by Classifying Reflected White Noise
We propose a novel fingering estimation method that allows a player to use any wind instrument as a music controller by attaching a single microphone and loudspeaker-embedded mouthpiece. The loudspeaker plays white noise continuously while the fingerings are estimated in real-time based on the sound pressure recorded at the end of the instrument. Our method addresses a major problem of conventional music controllers: differences in the tactile feel of keys compared to the player’s own instrument. We demonstrated that the proposed method accurately estimated fingerings on a saxophone with promising performance (a 1.05 % misclassification rate), satisfying the low-latency feedback required in the context of musical performance.