Subject: [AUDITORY] Final extended deadline for submitting to special collection of Music & Science on "Explaining Music with AI" From: David Meredith <dave@xxxxxxxx> Date: Tue, 30 Aug 2022 19:22:00 +0200=EF=BB=BFDear colleagues, We have decided to extend the deadline for submitting to our special collec= tion of the journal, Music & Science (https://journals.sagepub.com/home/mns)= on "Explaining Music with AI: Advancing the scientific understanding of mus= ic through computation". The new deadline is 12:00 noon GMT on Saturday 1 Oc= tober 2022. Please note that there will be no further extension to the deadline. We have included the final call below for your information. We very much look forward to receiving your submissions! Kind regards, Dave, Anja & Tom ********************************************************************** Final Call for Papers: Special Collection on Explaining music with AI: Advancing the scientific understanding of music through computation Final Extended Deadline for submission of full manuscripts:=20 12:00 noon GMT on Saturday 1 October 2022 Guest edited by David Meredith, Anja Volk & Tom Collins ********************************************************************** In recent years, a huge number of publications, particularly in the areas of music information retrieval and music generation, have reported on projects in which deep learning neural network models have been used successfully to carry out a wide variety of generation, regression and classification tasks on musical data. This work has significantly contributed to the arsenal of computational tools that we have at our disposal, if we want to explore, organise, create or simply enjoy digital music resources. However, the majority of such models are =E2=80=9Cblack box=E2=80=9D models that have thousands or even millions of free parameters, whose values are determined through training on, typically, large amounts of data. The computing pioneer, John von Neumann, allegedly joked, =E2=80=9CWith four free variables I can fit an elephant and with five I can make him wiggle his trunk=E2=80=9D (Freeman Dyson, 2004, =E2=80=9CA meeting with Enrico Fermi=E2=80=9D= , Nature, 427:297). Such considerations prompt us to question whether such black-box deep learning models make a significant contribution to our scientific understanding of music, musical processes and musical behaviour. For this special collection, we seek high quality contributions that report on recent research in which any computational method has been used to advance our understanding of how and why music is created, communicated and received. We are particularly interested in shining a light on computational methods that have perhaps not received the attention they deserve because of the dominance of deep learning in recent years. At the same time, contributions in which deep learning and other neural network models have been shown to advance the scientific understanding of music are also very welcome. Submissions may address any aspect of musical behaviour, including, but not limited to, composition, improvisation, performance, listening, musical gestures and dance. Contributions may also focus on any aspects of music, e.g., rhythm, harmony, melody, counterpoint, instrumentation or timbre. We likewise set no constraints on the considered music=E2=80=99s style, genre, period or place of origin. However, the reported work must have adopted a computational approach that has led to an advancement in our scientific understanding of music. We are also keen to cover a variety of application areas where music is put to use, not only for pure entertainment or artistic purposes, but also, for example, in healthcare, in rituals and ceremonies, in meditation, in film soundtracks or video games, or even, for example, in politics or advertising. We welcome, in particular, contributions where a computational approach has been employed in conjunction with methodologies and knowledge from other fields, such as psychology, musicology, sociology, biology, physics, anthropology or ethnomusicology. The deadline for submission of full manuscripts has been extended to ***12:00 noon GMT on Saturday 1 October 2022.*** Note that there will be no further extensions to this deadline. Instructions for authors of this Special Collection are available at: https://uk.sagepub.com/en-gb/eur/music-science/journal202491#submission-gui= delines We look forward to receiving your submission! David Meredith Department of Architecture, Design, and Media Technology, Aalborg University, Denmark Anja Volk Department of Information and Computing Sciences, Utrecht University, The Netherlands Tom Collins Department of Music, University of York, United Kingdom