{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:23:07Z","timestamp":1773246187915,"version":"3.50.1"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,11,1]],"date-time":"2019-11-01T00:00:00Z","timestamp":1572566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,11]]},"DOI":"10.1109\/apsipaasc47483.2019.9023314","type":"proceedings-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T17:03:54Z","timestamp":1583514234000},"page":"1250-1255","source":"Crossref","is-referenced-by-count":11,"title":["Mixture of CNN Experts from Multiple Acoustic Feature Domain for Music Genre Classification"],"prefix":"10.1109","author":[{"given":"Yang","family":"Yi","sequence":"first","affiliation":[]},{"given":"Kuan-Yu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Hung-Yan","family":"Gu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2017.2713830"},{"key":"ref11","article-title":"Representation learning of music using artist labels","author":"park","year":"0","journal-title":"Proc of ISMIR"},{"key":"ref12","first-page":"434","article-title":"Learning temporal features using a deep neural network and its application to music genre classification","author":"jeong","year":"0","journal-title":"Proc of ISMIR"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3095713.3095733"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.2478\/eletel-2014-0042"},{"key":"ref15","article-title":"Autoregressive MFCC models for genre classification improved by harmonic-percussion separation","author":"rump","year":"0","journal-title":"Proc of ISMIR"},{"key":"ref16","article-title":"Harmonic\/percussive separation using median filtering","author":"fitzgerald","year":"0","journal-title":"Proc DAFx"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952585"},{"key":"ref18","article-title":"A tutorial on deep learning for music information retrieval","author":"choi","year":"2017","journal-title":"ArXiv"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSA.2002.800560"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/SiPS.2013.6674516"},{"key":"ref27","article-title":"librosa: Audio and music signal analysis in python","author":"mcfee","year":"0","journal-title":"Proceedings of the 14th Python in Science Conference"},{"key":"ref3","first-page":"1505","article-title":"Automatic chord recognition for music classification and retrieval","author":"cheng","year":"0","journal-title":"Proc of IEEE International Conference on Multimedia and Expo"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6637646"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2006.884618"},{"key":"ref8","article-title":"Transfer learning for music classification and regression tasks","author":"choi","year":"0","journal-title":"Proc of ISMIR"},{"key":"ref7","article-title":"Explaining deep convolutional neural networks on music classification","author":"choi","year":"2016","journal-title":"ArXiv"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-14980-1_44"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682912"},{"key":"ref1","first-page":"11.4:670","article-title":"Automatic music genre classification based on modulation spectral analysis of spectral and cepstral features","author":"lee","year":"2009","journal-title":"IEEE Transactions on Multimedia"},{"key":"ref20","article-title":"The GTZAN dataset: its contents, its faults, their effects on evaluation, and its future use","author":"sturm","year":"2013","journal-title":"ArXiv"},{"key":"ref22","article-title":"Fma: a dataset for music analysis","author":"defferrard","year":"2016","journal-title":"ArXiv"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2478068"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2009.2036813"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8461628"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICDSP.2014.6900697"},{"key":"ref25","article-title":"Transfer learning by supervised pre-training for audio-based music classification","author":"van den oord","year":"0","journal-title":"Proc of ISMIR"}],"event":{"name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","location":"Lanzhou, China","start":{"date-parts":[[2019,11,18]]},"end":{"date-parts":[[2019,11,21]]}},"container-title":["2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8989870\/9023008\/09023314.pdf?arnumber=9023314","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T21:54:59Z","timestamp":1658094899000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9023314\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/apsipaasc47483.2019.9023314","relation":{},"subject":[],"published":{"date-parts":[[2019,11]]}}}