{"title":"Fault-Tolerant Music Search by New Ranking Order Algorithm","authors":"W. Theimer, Andree Ross","doi":"10.1109/MMSP.2006.285303","DOIUrl":null,"url":null,"abstract":"Music information retrieval is an active area of research with high practical relevance. Humming a melody is one natural way to overcome the input restrictions when searching for music. In this presentation we concentrate on a new ranking order algorithm to match melody input to a music database containing polyphonic music as sequences of notes. The new algorithm achieves high melody recognition rates and shows graceful degradation in the presence of errors such as omission/insertion of notes or wrong tone heights/durations. The recognition rate is maximized by applying evolutionary strategies for parameter optimizations. The parallel implementation on a Linux-based PC cluster and the computational effort are discussed. Quantitative results are presented for melody recognition. We compare the method with related work and conclude with an outlook","PeriodicalId":267577,"journal":{"name":"2006 IEEE Workshop on Multimedia Signal Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Workshop on Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2006.285303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Music information retrieval is an active area of research with high practical relevance. Humming a melody is one natural way to overcome the input restrictions when searching for music. In this presentation we concentrate on a new ranking order algorithm to match melody input to a music database containing polyphonic music as sequences of notes. The new algorithm achieves high melody recognition rates and shows graceful degradation in the presence of errors such as omission/insertion of notes or wrong tone heights/durations. The recognition rate is maximized by applying evolutionary strategies for parameter optimizations. The parallel implementation on a Linux-based PC cluster and the computational effort are discussed. Quantitative results are presented for melody recognition. We compare the method with related work and conclude with an outlook