{"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}
引用次数: 0
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.