{"title":"Tonal-based retrieval of Arabic and middle-east music by automatic makam description","authors":"Leonidas Ioannidis, E. Gómez, P. Herrera","doi":"10.1109/CBMI.2011.5972516","DOIUrl":null,"url":null,"abstract":"The automatic description of music from traditions that do not follow the Western notation and theory needs specifically designed tools. We investigate here the makams, which are scales in the modal music of Arabic and Middle East regions. We evaluate two approaches for classifying musical pieces from the ‘makam world’, according to their scale, by using chroma features extracted from polyphonic music signals. The first method compares the extracted features with a set of makam templates, while the second one uses trained classifiers. Both approaches provided good results (F-measure=0.69 and 0.73 respectively) on a collection of 302 pieces from 9 makam families. Furthermore, error analyses showed that certain confusions were musically coherent and that these techniques could complement each other in this particular context.","PeriodicalId":358337,"journal":{"name":"2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMI.2011.5972516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
The automatic description of music from traditions that do not follow the Western notation and theory needs specifically designed tools. We investigate here the makams, which are scales in the modal music of Arabic and Middle East regions. We evaluate two approaches for classifying musical pieces from the ‘makam world’, according to their scale, by using chroma features extracted from polyphonic music signals. The first method compares the extracted features with a set of makam templates, while the second one uses trained classifiers. Both approaches provided good results (F-measure=0.69 and 0.73 respectively) on a collection of 302 pieces from 9 makam families. Furthermore, error analyses showed that certain confusions were musically coherent and that these techniques could complement each other in this particular context.