{"title":"A compressed domain beat detector using MP3 audio bitstreams","authors":"Ye-Kui Wang, M. Vilermo","doi":"10.1145/500141.500172","DOIUrl":null,"url":null,"abstract":"This paper presents a novel beat detector that processes MPEG-1 Layer III (known as MP3) encoded audio bitstreams directly in the compressed domain. Most previous beat detection or tracking systems dealing with MIDI or PCM signals are not directly applicable to compressed audio bitstreams, such as MP3 bitstreams. We have developed the beat detector as a part of a beat-pattern based error concealment scheme for streaming music over error prone channels. Special effort was used to obtain a tailored trade-off between performance, complexity and memory consumption for this specific application. A comparison between the machine-detected results to the human annotation has shown that the proposed method correctly tracked beats in 4 out of 6 popular music test signals. The results were analyzed.","PeriodicalId":416848,"journal":{"name":"MULTIMEDIA '01","volume":"179 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MULTIMEDIA '01","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/500141.500172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 45
Abstract
This paper presents a novel beat detector that processes MPEG-1 Layer III (known as MP3) encoded audio bitstreams directly in the compressed domain. Most previous beat detection or tracking systems dealing with MIDI or PCM signals are not directly applicable to compressed audio bitstreams, such as MP3 bitstreams. We have developed the beat detector as a part of a beat-pattern based error concealment scheme for streaming music over error prone channels. Special effort was used to obtain a tailored trade-off between performance, complexity and memory consumption for this specific application. A comparison between the machine-detected results to the human annotation has shown that the proposed method correctly tracked beats in 4 out of 6 popular music test signals. The results were analyzed.