{"title":"Cover song recognition based on MPEG-7 audio features","authors":"R. M. F. Ponighzwa, R. Sarno, Dwi Sunaryono","doi":"10.1109/ICSITECH.2017.8257086","DOIUrl":null,"url":null,"abstract":"Lately, song industry has developed rapidly throughout the world. In the past, there were many applications which used song as their main themes, such as Shazam and Sound hound. Shazam and Sound hound could identify a song based on recorded one through the application. These applications work by matching the recorded song with an original song in the database. However, matching process is only based on the particular part of the spectrogram instead of an entire song's spectrogram. The disadvantages of this method arise though. This application could only identify the recorded original song. When application recorded a cover song, it cannot identify the title of the original song's since the spectrogram of a cover performance's and its original song's is entirely different. This paper exists to discuss how to recognize a cover song based on MPEG-7 standard ISO. KNN was used as classification method and combined with Audio Spectrum Projection and Audio Spectrum Flatness feature from MPEG-7 extraction. The result from this method identifies an original song from recorded cover of the original one. Result for experiment in this paper is about 75–80%, depends on testing data; whether the testing data is a dominant vocal song or dominant instrument song.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Science in Information Technology (ICSITech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSITECH.2017.8257086","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
Lately, song industry has developed rapidly throughout the world. In the past, there were many applications which used song as their main themes, such as Shazam and Sound hound. Shazam and Sound hound could identify a song based on recorded one through the application. These applications work by matching the recorded song with an original song in the database. However, matching process is only based on the particular part of the spectrogram instead of an entire song's spectrogram. The disadvantages of this method arise though. This application could only identify the recorded original song. When application recorded a cover song, it cannot identify the title of the original song's since the spectrogram of a cover performance's and its original song's is entirely different. This paper exists to discuss how to recognize a cover song based on MPEG-7 standard ISO. KNN was used as classification method and combined with Audio Spectrum Projection and Audio Spectrum Flatness feature from MPEG-7 extraction. The result from this method identifies an original song from recorded cover of the original one. Result for experiment in this paper is about 75–80%, depends on testing data; whether the testing data is a dominant vocal song or dominant instrument song.