MOTIVATION
Machine learning has permeated nearly every area of music informatics, driven by a profusion of recordings available in digital audio formats, steady improvements to the accessibility and quality of symbolic corpora, availability of powerful algorithms in standard machine learning toolboxes, and theoretical advances in machine learning and data mining. As complexity of the problems investigated by researchers on machine learning and music increases, there is a need to develop new algorithms and methods to solve these problems. As a consequence, research on machine learning and music is an active and growing field reflected in international meetings such as the International Workshops on Machine Learning and Music (MML): MML2008 (Helsinki, Finland), MML2009 (Bled, Slovenia), MML2010 (Florence, Italy), MML2011 (Sierra Nevada, Spain), MML2012 (Edinburgh, Scotland), MML2013 (Prague, Czech Republic), MML2014 (Barcelona, Spain), MML2015 (Vancouver, Canada), and MML2016 (Riva del Garda, Italy).
SPECIAL THEME: INTELLIGENT MUSIC LEARNING SYSTEMS
Machine learning holds great potential for enhancing music learning. For MML2017, in addition to general topics in music and machine learning, we warmly welcome contributions describing applications of machine learning for technology-enhanced music learning.
TOPICS Papers in all applications on music and machine learning are welcome, including but not limited to
Audio demonstrations are encouraged when indicated by the content of the paper. IMPORTAT DATES Paper Submission Deadline: July 3, 2017 Acceptance Notification: July 30, 2017 Final versions due: August 10, 2017 Workshop Date: October 6, 2017 SUBMISSIONS OF PAPERS Papers of up to 5 printed pages in LNCS format are welcome. Submissions will be evaluated according to their originality and relevance to the workshop, and should include author names, affiliations, contact information, and an abstract of 60-100 words. Contributions should be in PDF format and submitted by Easychair. LNCS format details can be found here.