{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T12:07:00Z","timestamp":1777896420337,"version":"3.51.4"},"reference-count":0,"publisher":"University of Zielona G\u00f3ra, Poland","issue":"1","license":[{"start":{"date-parts":[[2016,3,1]],"date-time":"2016-03-01T00:00:00Z","timestamp":1456790400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The problem of note onset detection in musical signals is considered. The proposed solution is based on known approaches in which an <jats:italic>onset detection function<\/jats:italic> is defined on the basis of spectral characteristics of audio data. In our approach, several onset detection functions are used simultaneously to form an input vector for a multi-layer non-linear perceptron, which learns to detect onsets in the training data. This is in contrast to standard methods based on thresholding the onset detection functions with a moving average or a moving median. Our approach is also different from most of the current machine-learning-based solutions in that we explicitly use the onset detection functions as an intermediate representation, which may therefore be easily replaced with a different one, e.g., to match the characteristics of a particular audio data source. The results obtained for a database containing annotated onsets for 17 different instruments and ensembles are compared with state-of-the-art solutions.<\/jats:p>","DOI":"10.1515\/amcs-2016-0014","type":"journal-article","created":{"date-parts":[[2016,4,2]],"date-time":"2016-04-02T17:45:06Z","timestamp":1459619106000},"page":"203-213","source":"Crossref","is-referenced-by-count":8,"title":["Note onset detection in musical signals via neural\u2013network\u2013based multi\u2013ODF fusion"],"prefix":"10.61822","volume":"26","author":[{"given":"Bart\u0142omiej","family":"Stasiak","sequence":"first","affiliation":[{"name":"Institute of Information Technology, \u0141\u00f3d\u017a University of Technology, ul. W\u00f3lcza\u0144ska 215, 90-924 \u0141\u00f3d\u017a, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u0119drzej","family":"Mo\u0144ko","sequence":"additional","affiliation":[{"name":"Institute of Information Technology, \u0141\u00f3d\u017a University of Technology, ul. W\u00f3lcza\u0144ska 215, 90-924 \u0141\u00f3d\u017a, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Niewiadomski","sequence":"additional","affiliation":[{"name":"Institute of Information Technology, \u0141\u00f3d\u017a University of Technology, ul. W\u00f3lcza\u0144ska 215, 90-924 \u0141\u00f3d\u017a, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"37438","published-online":{"date-parts":[[2016,3,31]]},"container-title":["International Journal of Applied Mathematics and Computer Science"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/content.sciendo.com\/view\/journals\/amcs\/26\/1\/article-p203.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/amcs-2016-0014","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T22:57:01Z","timestamp":1715813821000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/amcs-2016-0014"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,3,31]]},"published-print":{"date-parts":[[2016,3,1]]}},"alternative-id":["10.1515\/amcs-2016-0014"],"URL":"https:\/\/doi.org\/10.1515\/amcs-2016-0014","relation":{},"ISSN":["2083-8492"],"issn-type":[{"value":"2083-8492","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,3,1]]}}}