{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:56:11Z","timestamp":1776887771725,"version":"3.51.2"},"reference-count":42,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T00:00:00Z","timestamp":1685836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T00:00:00Z","timestamp":1685836800000},"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":[[2023,6,4]]},"DOI":"10.1109\/icassp49357.2023.10094943","type":"proceedings-article","created":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T13:28:30Z","timestamp":1683293310000},"page":"1-5","source":"Crossref","is-referenced-by-count":9,"title":["Hyperbolic Audio Source Separation"],"prefix":"10.1109","author":[{"given":"Darius","family":"Petermann","sequence":"first","affiliation":[{"name":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gordon","family":"Wichern","sequence":"additional","affiliation":[{"name":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aswin","family":"Subramanian","sequence":"additional","affiliation":[{"name":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan Le","family":"Roux","sequence":"additional","affiliation":[{"name":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Constant curvature graph convolutional networks","author":"bachmann","year":"2020","journal-title":"Proc ICML"},{"key":"ref35","article-title":"Geoopt: Riemannian optimization in PyTorch","author":"kochurov","year":"2020"},{"key":"ref12","article-title":"Hyperbolic graph neural networks","author":"liu","year":"2019","journal-title":"Proc NeurIPS"},{"key":"ref34","article-title":"Riemannian adaptive stochastic gradient algorithms on matrix manifolds","author":"kasai","year":"2019","journal-title":"Proc ICML"},{"key":"ref15","article-title":"From trees to continuous embeddings and back: Hyperbolic hierarchical clustering","author":"chami","year":"2020","journal-title":"Proc NeurIPS"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462507"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00645"},{"key":"ref36","article-title":"SDR– half-baked or well done?","author":"le roux","year":"2019","journal-title":"Proc ICASSP"},{"key":"ref31","article-title":"Hyperbolic deep neural networks: A survey","volume":"12","author":"peng","year":"2021","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref30","article-title":"Evaluating bayesian deep learning methods for semantic segmentation","author":"mukhoti","year":"2018"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450101"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/WASPAA.2019.8937170"},{"key":"ref10","article-title":"Hyperbolic neural networks++","author":"shimizu","year":"2021","journal-title":"Proc ICLR"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178964"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7471631"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178061"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00441"},{"key":"ref39","article-title":"Poincaré embeddings for learning hierarchical representations","volume":"30","author":"nickel","year":"2017","journal-title":"Proc NeurIPS"},{"key":"ref16","article-title":"Free hyperbolic neural networks with limited radii","author":"guo","year":"2022","journal-title":"Proc CVPR"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2018-1629"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01242"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00263"},{"key":"ref24","article-title":"Hierarchical musical instrument separation","author":"manilow","year":"2020","journal-title":"Proc ISMIR"},{"key":"ref23","article-title":"Leveraging hierarchical structures for few-shot musical instrument recognition","author":"garcia","year":"2021","journal-title":"Proc ISMIR"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.23919\/APSIPAASC55919.2022.9980158"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3129695"},{"key":"ref20","article-title":"Representation tradeoffs for hyperbolic embeddings","author":"sala","year":"2018","journal-title":"Proc ICML"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICSPCS.2018.8631773"},{"key":"ref41","article-title":"Dropout as a Bayesian approximation: Representing model uncertainty in deep learning","author":"gal","year":"2015","journal-title":"Proc ICML"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2006.1661401"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25878-7_34"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9052908"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682341"},{"key":"ref29","article-title":"Hyperbolic neural networks","volume":"31","author":"ganea","year":"2018","journal-title":"Proc NeurIPS"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2018.2795749"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747314"},{"key":"ref9","article-title":"Generalization error bound for hyperbolic ordinal embedding","author":"suzuki","year":"2021","journal-title":"Proc ICML"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2018.2842159"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2019.2915167"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9052981"},{"key":"ref5","article-title":"Hybrid spectrogram and waveform source separation","author":"d\u00e9fossez","year":"2021","journal-title":"Proc ISMIR Workshop on Music Source Separation"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"1462","DOI":"10.1109\/TSA.2005.858005","article-title":"Performance measurement in blind audio source separation","volume":"14","author":"vincent","year":"2006","journal-title":"IEEE Trans Audio Speech Lang Process"}],"event":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Rhodes Island, Greece","start":{"date-parts":[[2023,6,4]]},"end":{"date-parts":[[2023,6,10]]}},"container-title":["ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10094559\/10094560\/10094943.pdf?arnumber=10094943","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T14:01:36Z","timestamp":1699884096000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10094943\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,4]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/icassp49357.2023.10094943","relation":{},"subject":[],"published":{"date-parts":[[2023,6,4]]}}}