{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T19:35:32Z","timestamp":1730230532943,"version":"3.28.0"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"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":[[2021,6,6]]},"DOI":"10.1109\/icassp39728.2021.9413358","type":"proceedings-article","created":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T15:53:45Z","timestamp":1620921225000},"page":"46-50","source":"Crossref","is-referenced-by-count":4,"title":["Transcription Is All You Need: Learning To Separate Musical Mixtures With Score As Supervision"],"prefix":"10.1109","author":[{"given":"Yun-Ning","family":"Hung","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gordon","family":"Wichern","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Le Roux","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","first-page":"626","article-title":"SDR– half-baked or well done?","author":"le roux","year":"2019","journal-title":"Proc ICASSP"},{"key":"ref32","first-page":"84","article-title":"Intuitive analysis, creation and manipulation of midi data with pretty midi","author":"raffel","year":"2014","journal-title":"ISMIR Late Breaking and Demo Papers"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2019.2915167"},{"article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","year":"2018","author":"bai","key":"ref30"},{"key":"ref34","first-page":"367","article-title":"mir_eval: A transparent implementation of common mir metrics","volume":"15","author":"raffel","year":"2014","journal-title":"Proc ISMIR"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/8363507"},{"key":"ref11","first-page":"569","article-title":"Monaural score-informed source separation for classical music using convolutional neural networks","volume":"18","author":"miron","year":"2017","journal-title":"Proc ISMIR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952562"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683800"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/WASPAA.2019.8937266"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2019.2929440"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2020.3013105"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053921"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053396"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00398"},{"key":"ref28","article-title":"Learning features of music from scratch","author":"thickstun","year":"2017","journal-title":"Proc ICLR"},{"key":"ref4","first-page":"776","article-title":"Audio set: An ontology and human-labeled dataset for audio events","author":"gemmeke","year":"2017","journal-title":"Proc ICASSP"},{"key":"ref27","first-page":"309","article-title":"Escaping from the abyss of manual annotation: New methodology of building polyphonic datasets for automatic music transcription","author":"su","year":"2015","journal-title":"Proc CMMR"},{"key":"ref3","first-page":"155","article-title":"Medleydb: A multitrack dataset for annotation-intensive mir research","volume":"14","author":"bittner","year":"2014","journal-title":"Proc ISMIR"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683426"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/WASPAA.2019.8937170"},{"key":"ref5","first-page":"591","article-title":"The million song dataset","author":"bertin-mahieux","year":"2011","journal-title":"Proc ISMIR"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/app8050654"},{"key":"ref7","article-title":"Learning-based methods for comparing sequences, with applications to audio-to-midi alignment and matching","author":"raffel","year":"2016","journal-title":"Ph D Dissertation"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1109\/TASL.2009.2026503","article-title":"On the improvement of singing voice separation for monaural recordings using the MIR-1K dataset","volume":"18","author":"hsu","year":"2010","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054340"},{"article-title":"The MUSDB18 corpus for music separation","year":"2017","author":"rafii","key":"ref1"},{"key":"ref20","first-page":"570","article-title":"The sound of pixels","author":"zhao","year":"2018","journal-title":"Proc ECCV"},{"key":"ref22","first-page":"2391","article-title":"Adversarial semi-supervised audio source separation applied to singing voice ex-traction","author":"stoller","year":"2018","journal-title":"Proc ICASSP"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/636"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682443"},{"article-title":"Denoising without access to clean data using a partitioned autoencoder","year":"2015","author":"stowell","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2010.2042119"},{"journal-title":"Fundamentals of Music Processing Audio Analysis Algorithms Applications","year":"2015","author":"m\u00fcller","key":"ref25"}],"event":{"name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2021,6,6]]},"location":"Toronto, ON, Canada","end":{"date-parts":[[2021,6,11]]}},"container-title":["ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9413349\/9413350\/09413358.pdf?arnumber=9413358","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T11:40:51Z","timestamp":1652182851000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9413358\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,6]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/icassp39728.2021.9413358","relation":{},"subject":[],"published":{"date-parts":[[2021,6,6]]}}}