{"id":19814,"date":"2026-03-25T13:47:54","date_gmt":"2026-03-25T12:47:54","guid":{"rendered":"https:\/\/www.lehre.fau.de\/?p=19814"},"modified":"2026-04-22T11:16:20","modified_gmt":"2026-04-22T09:16:20","slug":"%f0%9f%8e%a5ai-as-co-creator-fostering-reflective-use-of-ai-and-building-foundational-skills-in-music-and-audio-analysis","status":"publish","type":"post","link":"https:\/\/www.lehre.fau.de\/en\/%f0%9f%8e%a5ai-as-co-creator-fostering-reflective-use-of-ai-and-building-foundational-skills-in-music-and-audio-analysis\/","title":{"rendered":"\ud83c\udfa5AI as Co-Creator \u2013 Fostering Reflective Use of AI and Building Foundational Skills in Music and Audio Analysis"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\" id=\"block-5cbe01d2-4d14-48b8-b7c3-0eea639ba827\">Description<\/h2>\n\n\n\n<p id=\"block-52fc72fb-25b2-4124-aa43-b3c00f660d6f\">Prof. Dr. Meinard M\u00fcller, Chair of Semantic Audio Signal Processing at the International Audio Laboratories in Erlangen, integrates AI methods holistically into research and teaching. The focus is not merely on the application of AI tools, but on understanding the entire process chain: from musical applications and mathematical modeling to implementation, the training of neural networks, and the critical evaluation of their results.<\/p>\n\n\n\n<p>Students learn not to use AI as a black box, but to understand it as a tool that opens up new possibilities in music and audio signal processing. At the same time, Prof. M\u00fcller raises awareness of the risks posed by flawed data, distorted annotations, and superficial use of AI.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p id=\"block-4f922e77-6d5f-42f5-8142-0bf33c172075\"><strong>\u201eWe should neither glorify nor demonize AI. To me, AI is a tool\u2014but a very powerful one!\u201c<\/strong> &#8211; Prof. Dr. Meinard M\u00fcller<\/p>\n<\/blockquote>\n\n\n<div class=\"wp-block-rrze-elements-collapsibles \"><div class=\"accordion\">\n<div class=\"wp-block-rrze-elements-collapse \"><div class=\"accordion-group \"><h2 class=\"accordion-heading\"><button class=\"accordion-toggle\" data-toggle=\"collapse\" data-name=\"overview\" data-href=\"#overview\" type=\"button\" aria-expanded=\"false\" aria-controls=\"overview-section\" id=\"overview\">Overview<\/button><\/h2><div id=\"overview-section\" class=\"accordion-body \" aria-labelledby=\"overview\" role=\"region\" name=\"overview\"><div class=\"accordion-inner clearfix\">\n\n<h5 class=\"wp-block-heading\">Faculty<\/h5>\n\n\n\n<p>Faculty of Engineering, International Audio Laboratories Erlangen (FAU &amp; Fraunhofer IIS)<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Funded by<\/h5>\n\n\n\n<p>KIKomp<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Courses<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>lecture<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Target group<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Master<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Educational activities<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>engage\/motivate<\/li>\n\n\n\n<li>support\/communicate<\/li>\n\n\n\n<li>explain\/present<\/li>\n\n\n\n<li>review\/evaluate<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Digital tools<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Projet manager<\/h5>\n\n\n\n<p>Prof. Dr. Meinard M\u00fcller<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Keywords<\/h5>\n\n\n\n<p>AI<\/p>\n\n<\/div><\/div><\/div><\/div>\n<\/div><\/div>\n\n<div class=\"rrze-video-container\" data-video-id=\"rrze-video-69f59a580616b\"><div class=\"rrze-video rrze-video-container \">\n<div class=\"youtube-video plyr-videonum-1\" itemscope itemtype=\"https:\/\/schema.org\/Movie\">\n<meta itemprop=\"name\" content=\"FAU Lehre Good Practice IProf. Dr. Meinard M\u00fcller I KI f\u00fcr den Kompetenzaufbau reflektiert einsetzen\">\n<meta itemprop=\"director\" content=\"FAU Kompetenzzentrum Lehre\">\n<meta itemprop=\"provider\" content=\"YouTube\">\n<meta itemprop=\"thumbnailUrl\" content=\"https:\/\/i.ytimg.com\/vi\/zGbUtOx-6Ss\/hqdefault.jpg\">\n<meta itemprop=\"version\" content=\"1.0\">\n<div class=\"plyr__video-embed\">\n<iframe\n title=\"FAU Lehre Good Practice IProf. Dr. Meinard M\u00fcller I KI f\u00fcr den Kompetenzaufbau reflektiert einsetzen\"\n  src=\"https:\/\/www.youtube-nocookie.com\/embed\/zGbUtOx-6Ss?rel=0&#038;showinfo=0&#038;iv_load_policy=3&#038;modestbranding=1\"\n frameborder=\"0\"\n  allowfullscreen\n  allowtransparency\n  allow=\"autoplay\"\n><\/iframe>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n<h2 class=\"wp-block-heading\" id=\"block-240d2fe5-05df-4c7e-917f-f7534a5382a1\">Initial scenario<\/h2>\n\n\n\n<p id=\"block-9732b804-b7aa-4bf0-b814-167011ae485e\">With the increasing prevalence of neural networks, music and audio signal processing has become more complex. Today\u2019s students need skills across multiple disciplines: mathematics, signal processing, programming, data annotation, software and hardware infrastructure, as well as the ability to critically evaluate results.<\/p>\n\n\n\n<p id=\"block-9732b804-b7aa-4bf0-b814-167011ae485e\">The challenge: This broad spectrum of skills can easily be overwhelming. At the same time, the high performance of AI tools tempts users to solve problems too quickly using a \u201cblack box\u201d approach, without fully understanding the task at hand, data quality, or model limitations.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"block-599e0d08-c9d2-4295-b447-94d70989d409\">Objectives<\/h2>\n\n\n\n<p>The central goals of Prof. M\u00fcller\u2019s teaching concept are the development of in-depth competencies and the reflective application of AI methods:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Students should understand the entire process chain: from application scenarios to mathematical modeling and implementation.<\/li>\n\n\n\n<li>AI is taught as a tool that has flaws, makes assumptions, and must be questioned.<\/li>\n\n\n\n<li>Data quality, annotations, and plausibility checks are established as core competencies.<\/li>\n\n\n\n<li>The teaching aims to empower students not only to use AI results but also to critically evaluate and explain them.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"block-0c6dfde5-d247-4357-9fc9-a8b8d792c2b2\">Concepts, Implementation, Methods<\/h2>\n\n\n\n<p id=\"block-0b5a4bed-985a-4c8b-84b7-098bacee3287\">Prof. M\u00fcller\u2019s teaching follows a clearly structured sequence of skills: First, a musical task is defined (e.g., beat tracking or tempo detection), then mathematically modeled, implemented, trained using annotated data, and experimentally evaluated. In the process, students learn that problems often stem not from implementation but from data errors, biased annotations, or probabilistic training effects. To ensure a deep understanding, Prof. M\u00fcller deliberately separates the acquisition of fundamentals (mathematical models, data comprehension, logical reasoning) from the practical use of modern AI tools. In some teaching situations, therefore, work is done without computers\u2014in a circle of chairs, at the blackboard, through analog discussions\u2014to clearly articulate core concepts. AI tools such as ChatGPT are not prohibited but are used context-sensitively: routine tasks may be performed with AI support, but M\u00fcller deliberately refrains from using them when building competencies (e.g., academic writing, algorithmic thinking).<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p id=\"block-023ca829-4a2e-4269-a11b-d9a0475d2ccf\"><strong>\u201eMany people use deep learning without fully understanding the problem at hand. That is exactly what I strive to address in my teaching.\u201c<\/strong> &#8211; Prof. Dr. Meinard M\u00fcller<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"block-621fbedf-0ba2-41ca-a92c-ee35ec2a4758\">Experiences<\/h2>\n\n\n\n<ul id=\"block-9cd0ee43-bdd4-4446-af3d-cfc5d2049e1e\" class=\"wp-block-list\">\n<li>Students value AI tools but often use them too early\u2014before they fully understand the task at hand and the quality of the data.<\/li>\n\n\n\n<li>The most critical errors arise from insufficient or distorted data; AI reliably reproduces these distortions.<\/li>\n\n\n\n<li>Oral exams and in-person code reviews are particularly effective at revealing actual competencies.<\/li>\n\n\n\n<li>Consciously alternating between analog and digital teaching methods strengthens understanding of abstract concepts.<\/li>\n\n\n\n<li>AI-supported routine tasks reduce the workload but must not replace core learning processes.<\/li>\n<\/ul>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p id=\"block-86dc1bf2-0e6d-45d6-bc12-809223530897\"><strong>\u201eWithin a few minutes of talking, I can tell what has actually been understood\u2014and what was just churned out by an AI ghostwriter.\u201c<\/strong> &#8211; Prof. Dr. Meinard M\u00fcller<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"block-371ae602-92c0-4f0c-ab03-843374bf8d79\">Criteria for success<\/h2>\n\n\n\n<ul id=\"block-a4c16898-e49b-4d7e-a4e3-6a8b7d6e99c9\" class=\"wp-block-list\">\n<li>Students can explain AI methods rather than merely applying them\u2014including mathematical foundations and data dependencies.<\/li>\n\n\n\n<li>AI results are always evaluated against one\u2019s own expectations and through plausibility checks.<\/li>\n\n\n\n<li>Data annotation and preparation are recognized as core professional competencies.<\/li>\n\n\n\n<li>The connection between research and teaching is becoming closer: new developments are incorporated into teaching in a timely manner without neglecting the fundamentals.<\/li>\n<\/ul>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p id=\"block-86dc1bf2-0e6d-45d6-bc12-809223530897\">&#8220;<strong>Only those who understand the problem statement and the data can properly evaluate AI results.\u201c<\/strong> &#8211; Prof. Dr. Meinard M\u00fcller<\/p>\n<\/blockquote>\n\n\n\n<p id=\"block-19cd9670-b508-4291-98af-c1a3f45702bf\"><\/p>\n\n\n\n<p id=\"block-c1f56404-f397-4b77-b6af-14b758c70e19\"><a class=\"rrze-elements standard-btn primary-btn\" href=\"\/infothek\/good-practice\/\"><span> <svg height=\"1em\" width=\"1em\" class=\"rrze-elements-icon\" style=\"font-size: 1em;\"  aria-hidden=\"true\" focusable=\"false\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><!--! Font Awesome Free 6.6.0 by @fontawesome - https:\/\/fontawesome.com License - https:\/\/fontawesome.com\/license\/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2024 Fonticons, Inc. --><path fill=\"currentcolor\" d=\"M9.4 233.4c-12.5 12.5-12.5 32.8 0 45.3l160 160c12.5 12.5 32.8 12.5 45.3 0s12.5-32.8 0-45.3L109.2 288 416 288c17.7 0 32-14.3 32-32s-14.3-32-32-32l-306.7 0L214.6 118.6c12.5-12.5 12.5-32.8 0-45.3s-32.8-12.5-45.3 0l-160 160z\"\/><\/svg> Back to overview<\/span><\/a><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Description Prof. Dr. Meinard M\u00fcller, Chair of Semantic Audio Signal Processing at the International Audio Laboratories in Erlangen, integrates AI methods holistically into research and teaching. The focus is not merely on the application of AI tools, but on understanding the entire process chain: from musical applications and mathematical modeling to implementation, the training of [&hellip;]<\/p>\n","protected":false},"author":5579,"featured_media":19897,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_rrze_cache":"enabled","expiration_date":"","expiration_date_gmt":"","expiration_enabled":false,"_rrze_multilang_single_locale":"en_US","_rrze_multilang_single_source":"https:\/\/www.lehre.fau.de\/?p=12301","footnotes":""},"categories":[49,65],"tags":[],"class_list":["post-19814","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-good-practice","category-ki","en-US"],"_links":{"self":[{"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/posts\/19814","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/users\/5579"}],"replies":[{"embeddable":true,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/comments?post=19814"}],"version-history":[{"count":3,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/posts\/19814\/revisions"}],"predecessor-version":[{"id":21957,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/posts\/19814\/revisions\/21957"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/media\/19897"}],"wp:attachment":[{"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/media?parent=19814"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/categories?post=19814"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.lehre.fau.de\/wp-json\/wp\/v2\/tags?post=19814"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}