Dear colleagues, Please find below the second call for papers for a special collection of Music & Science on the topic of "Explaining Music with AI: Advancing the scientific understanding of music through computation". The deadline for submission of full manuscripts is ***Wednesday 31 August 2022***. If you think you may be submitting a paper, we would very much appreciate receiving an _expression_ of interest from you that provides the following information: * Draft title * Names, full contact details and affiliations of authors * 200 word overview of the expected content of the paper * References to any recent related publications by the authors (including any recent conference papers on a related topic) We would like to receive this EoI as soon as possible, so that we can have an idea of how many submissions we are likely to receive. The EoI is not in any way binding - it is just to help us with our planning of the collection. If you have any questions regarding this special collection, please contact the guest editors at dave@xxxxxxxxxxxxx. The official call for the collection is here: https://journals.sagepub.com/page/mns/special-collections/explaining-music-with-ai We look forward to receiving your submission! Kind regards, Dave, Anja and Tom ********************************************************************** Second Call for Papers: Special Collection on Explaining music with AI: Advancing the scientific understanding of music through computation Deadline for submission of full manuscripts: Wednesday 31 August 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 “black box” 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, “With four free variables I can fit an elephant and with five I can make him wiggle his trunk” (Freeman Dyson, 2004, “A meeting with Enrico Fermi”, 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’s 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. If you are interested in submitting a manuscript for this Special Collection, please send an _expression_ of interest to the guest editors (at dave@xxxxxxxxxxxxx), containing the following information: * Draft title * Names, full contact details and affiliations of authors * 200 word overview of the expected content of the paper * References to any recent related publications by the authors (including any recent conference papers on a related topic) Please send this _expression_ of interest as soon as possible, as it will help the editors to plan the special issue The deadline for submission of full manuscripts is *** Wednesday 31 August 2022 *** Instructions for authors of this Special Collection are available at: https://uk.sagepub.com/en-gb/eur/music-science/journal202491#submission-guidelines 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 |