{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:16:50Z","timestamp":1781194610943,"version":"3.54.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Denoising Diffusion Probabilistic Models (DDPMs) have made great strides in generating high-quality samples in both discrete and continuous domains.\n\nHowever, Discrete DDPMs (D3PMs) have yet to be applied to the domain of Symbolic Music.\n\nThis work presents the direct generation of Polyphonic Symbolic Music using D3PMs.\n\nOur model exhibits state-of-the-art sample quality, according to current quantitative evaluation metrics, and allows for flexible infilling at the note level.\n\nWe further show, that our models are accessible to post-hoc classifier guidance, widening the scope of possible applications.\n\nHowever, we also cast a critical view on quantitative evaluation of music sample quality via statistical metrics, and present a simple algorithm that can confound our metrics with completely spurious, non-musical samples.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/648","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T04:31:30Z","timestamp":1691728290000},"page":"5842-5850","source":"Crossref","is-referenced-by-count":14,"title":["Discrete Diffusion Probabilistic Models for Symbolic Music Generation"],"prefix":"10.24963","author":[{"given":"Matthias","family":"Plasser","sequence":"first","affiliation":[{"name":"Johannes Kepler University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvan","family":"Peter","sequence":"additional","affiliation":[{"name":"Johannes Kepler University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gerhard","family":"Widmer","sequence":"additional","affiliation":[{"name":"Johannes Kepler University"},{"name":"Linz Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","theme":"Artificial Intelligence","location":"Macau, SAR China","acronym":"IJCAI-2023","number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2023,8,19]]},"end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T04:53:00Z","timestamp":1691729580000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/648"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/648","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}