{"title":"Music Question Answering:Cognize and Perceive Music","authors":"Wenhao Gao, Xiaobing Li, Cong Jin, Tie Yun","doi":"10.1109/ICMEW56448.2022.9859499","DOIUrl":null,"url":null,"abstract":"Music analysis and understanding has always been the work of professionals. In order to help ordinary people congnize and perceive music, we put forward the Music Question Answering task in this paper. The goal of this task is to provide accurate answers given music and related questions. To this end, we made MQAdataset based on MagnaTagATune, which contains seven basic categories. According to the main source of the questions, all questions are divided into basic questions and depth questions. We tested on several models and analyzed the experimental results. The best model, Musicnn-MALiMo (Spectrogram,i=4), obtained 71.13% accuracy.","PeriodicalId":106759,"journal":{"name":"2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW56448.2022.9859499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Music analysis and understanding has always been the work of professionals. In order to help ordinary people congnize and perceive music, we put forward the Music Question Answering task in this paper. The goal of this task is to provide accurate answers given music and related questions. To this end, we made MQAdataset based on MagnaTagATune, which contains seven basic categories. According to the main source of the questions, all questions are divided into basic questions and depth questions. We tested on several models and analyzed the experimental results. The best model, Musicnn-MALiMo (Spectrogram,i=4), obtained 71.13% accuracy.