{"id":17340,"date":"2021-02-16T10:01:26","date_gmt":"2021-02-16T10:01:26","guid":{"rendered":"http:\/\/cio.edu.umh.es\/?p=17340"},"modified":"2021-07-22T09:49:52","modified_gmt":"2021-07-22T07:49:52","slug":"deep-learning-architectures-for-music-audio-classification-a-personal-review","status":"publish","type":"post","link":"https:\/\/cio.umh.es\/en\/2021\/02\/16\/deep-learning-architectures-for-music-audio-classification-a-personal-review\/","title":{"rendered":"Deep learning architectures for music audio classification: a personal (re)view"},"content":{"rendered":"<p>[:es]<b>T\u00edtulo:\u00a0<\/b>\u00a0Deep learning architectures for music audio classification: a personal (re)view<\/p>\n<p><b>Ponente:\u00a0<\/b>Jordi Pons i Puig (Dolby Laboratories)<\/p>\n<p><b><strong>Organizador:<\/strong>\u00a0<\/b>J<span class=\"gmail_default\">es\u00fas Javier Rodr\u00edguez Sala<\/span><\/p>\n<p><strong><span lang=\"EN-US\">Date:\u00a0<\/span><\/strong><span lang=\"EN-US\">Martes\u00a023\u00a0<\/span><span lang=\"EN-US\">de febrero de 2021 a las 12:00 horas.<\/span><\/p>\n<p><strong>Lugar:<\/strong>\u00a0\u00a0Online.\u00a0[button link=\u00bbhttps:\/\/meet.google.com\/toj-jchk-ahh\u00bb\u00a0color=\u00bbred\u00bb] PINCHA AQU\u00cd PARA ACCEDER[\/button]<\/p>\n<p><b>Abstract:\u00a0<\/b>A brief review of the state-of-the-art in music informatics research and deep learning reveals that such models achieved competitive results for several music-related tasks. In this talk I will provide insights in which deep learning architectures are (according to our experience) performing the best for audio classification. To this end, I will first introduce a review of the available front-ends (the part of the model that interacts with the input signal in order to map it into a latent-space) and back-ends (the part predicting the output given the representation obtained by the front-end). And finally, in order to discuss previously introduced front-ends and back-ends, I will present some cases we found throughout our path researching which deep learning architectures work best for music audio tagging.[:]<\/p>","protected":false},"excerpt":{"rendered":"<p>[:es]T\u00edtulo:\u00a0\u00a0Deep learning architectures for music audio classification: a personal (re)view<br \/>\nPonente:\u00a0Jordi Pons i Puig (Dolby Laboratories)<br \/>\nOrganizador:\u00a0Jes\u00fas Javier Rodr\u00edguez Sala<br \/>\nFecha:\u00a0Martes\u00a023\u00a0de febrero de 2021 a las 12:00 horas.<br \/>\nLugar:\u00a0\u00a0Online.\u00a0[button link=\u00bbhttps:\/\/meet.google.com\/toj-jchk-ahh\u00bb\u00a0color=\u00bbred\u00bb] PINCHA AQU\u00cd PARA ACCEDER[\/button]<br \/>\nAbstract:\u00a0A brief review of the state-of-the-art in music informatics research and deep learning reveals that such models achieved competitive results for several music-related tasks. In this [&#8230;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[4,873],"tags":[],"_links":{"self":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts\/17340"}],"collection":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/comments?post=17340"}],"version-history":[{"count":0,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts\/17340\/revisions"}],"wp:attachment":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/media?parent=17340"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/categories?post=17340"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/tags?post=17340"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}