Author: Benjamin Daniel | School of Humanities, Arts, and Social Sciences<\/p>\n
A new, multidisciplinary MIT\u00a0graduate program in music technology and computation<\/a> will feature faculty, labs, and curricula from across the Institute.<\/p>\n The program is a collaboration between the Music and Theater Arts Section<\/a> in the School of Humanities, Arts, and Social Sciences (SHASS); Department of Electrical Engineering and Computer Science<\/a> (EECS) in the School of Engineering<\/a>; and the MIT Schwarzman College of Computing<\/a>.<\/p>\n \u201cThe launch of a new graduate program in music technology strikes me as both a necessary and a\u00a0provocative gesture \u2014 an important leap in an era being rapidly redefined by exponential growth in computation, artificial intelligence, and human-computer interactions of every conceivable kind,\u201d\u00a0says\u00a0Jay Scheib<\/a>,\u200b\u200b head of the MIT Music and Theater Arts Section and the Class of 1949 Professor.<\/p>\n \u201cMusic plays an elegant role at the fore of a remarkable convergence of art and technology,\u201d adds Scheib. \u201cIt\u2019s the right time to launch this program and if not at MIT, then where?\u201d<\/p>\n MIT\u2019s practitioners define music technology as the field of scientific inquiry where they study, discover, and develop new computational approaches to music that include music information retrieval; artificial intelligence; machine learning; generative algorithms; interaction and performance systems; digital instrument design; conceptual and perceptual modeling of music; acoustics; audio signal processing; and software development for creative expression and music applications.<\/p>\n Eran Egozy<\/a>, professor of the practice in music technology and one of the program leads, says MIT\u2019s focus is technical research in music technology that always centers the humanistic and artistic aspects of making music.<\/p>\n \u201cThere are so many MIT students who are fabulous musicians,\u201d says Egozy. \u201cWe’ll approach music technology as computer scientists, mathematicians, and musicians.\u201d<\/p>\n With the launch of this new program \u2014 an offering alongside those available in MIT\u2019s\u00a0Media Lab<\/a> and elsewhere \u2014 Egozy sees MIT becoming the obvious destination for students interested in music and computation study, preparing high-impact graduates for roles in academia and industry, while also helping mold creative, big-picture thinkers who can tackle large challenges.<\/p>\n Investigating big ideas<\/strong><\/p>\n The program will encompass two master\u2019s degrees and a PhD:<\/p>\n Anna Huang<\/a>, a new MIT assistant professor who holds a shared faculty position between the MIT Music and Theater Arts Section and the MIT Schwarzman College of Computing, is collaborating with Egozy to develop and launch the program. Huang arrived at MIT this fall after spending eight years with Magenta at Google Brain and DeepMind, spearheading efforts in generative modeling, reinforcement learning, and human-computer interaction to support human-AI partnerships in music-making.<\/p>\n \u201cAs a composer turned AI researcher who specializes in generative music technology, my long-term goal is to develop AI systems that can shed new light on how we understand, learn, and create music, and to learn from interactions between musicians in order to transform how we approach human-AI collaboration,\u201d says Huang. \u201cThis new program will let us further investigate how musical applications can illuminate problems in understanding neural networks, for example.\u201d<\/p>\n MIT\u2019s new Edward and Joyce Linde Music Building<\/a>, featuring\u00a0enhanced music technology spaces, will also help transform music education with versatile performance venues and optimized rehearsal facilities.<\/p>\n A natural home for music technology<\/strong><\/p>\n MIT\u2019s world-class, top-ranked engineering program, combined with its focus on computation and its conservatory-level music education offerings, makes the Institute a natural home for the continued expansion of music technology education.<\/p>\n The collaborative nature of the new program is the latest example of interdisciplinary work happening across the Institute.<\/p>\n \u201cI am thrilled that the School of Engineering is partnering with the MIT Music and Theater Arts Section on this important initiative, which represents the convergence of various engineering areas \u2014 such as AI and design \u2014 with music,\u201d says Anantha Chandrakasan<\/a>, dean of the School of Engineering, chief innovation and strategy officer, and the Vannevar Bush Professor of EECS. \u201cI can\u2019t wait to see the innovative projects the students will create and how they will drive this new field forward.\u201d<\/p>\n \u201cEveryone on campus knows that MIT is a great place to do music. But I want people to come to MIT because of what we do in music,\u201d says Agustin Rayo<\/a>, the Kenan Sahin Dean of SHASS. \u201cThis outstanding collaboration with the Schwarzman College of Computing and the School of Engineering will make that dream a reality, by bringing together the world\u2019s best engineers with our extraordinary musicians to create the next generation of music technologies.\u201d<\/p>\n \u201cThe new master\u2019s program offers students an unparalleled opportunity to explore the intersection of music and technology,\u201d says Daniel Huttenlocher<\/a>, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of EECS. \u201cIt equips them with a deep understanding of this confluence, preparing them to advance new approaches to computational models of music and be at the forefront of an evolving area.\u201d\u00a0<\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Author: Benjamin Daniel | School of Humanities, Arts, and Social Sciences A new, multidisciplinary MIT\u00a0graduate program in music technology and computation will feature faculty, labs, […] Read More<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":457,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[24],"tags":[],"_links":{"self":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/7633"}],"collection":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/comments?post=7633"}],"version-history":[{"count":0,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/7633\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media\/459"}],"wp:attachment":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media?parent=7633"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/categories?post=7633"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/tags?post=7633"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n