The Effect of Explicit Structure Encoding of Deep Neural Networks for Symbolic Music Generation

With recent breakthroughs in artificial neural networks, deep generative models have become one of the leading techniques for computational creativity. Despite very promising progress on image and short sequence generation, symbolic music generation remains a challenging problem since the structure of compositions are usually complicated. In this study, we attempt to solve the melody generation problem constrained by the given chord progression. This music meta-creation problem can also be incorporated into a plan recognition system with user inputs and predictive structural outputs. In particular, we explore the effect of explicit architectural encoding of musical structure via comparing two sequential generative models: LSTM (a type of RNN) and WaveNet (dilated temporal-CNN). As far as we know, this is the first study of applying WaveNet to symbolic music generation, as well as the first systematic comparison between temporal-CNN and RNN for music generation. We conduct a survey for evaluation in our generations and implemented Variable Markov Oracle in music pattern discovery. Experimental results show that to encode structure more explicitly using a stack of dilated convolution layers improved the performance significantly, and a global encoding of underlying chord progression into the generation procedure gains even more.Comment: 8 pages, 13 figure

Finding new music: a diary study of everyday encounters with novel songs

This paper explores how we, as individuals, purposefully or serendipitously encounter 'new music' (that is, music that we haven’t heard before) and relates these behaviours to music information retrieval activities such as music searching and music discovery via use of recommender systems. 41 participants participated in a three-day diary study, in which they recorded all incidents that brought them into contact with new music. The diaries were analyzed using a Grounded Theory approach. The results of this analysis are discussed with respect to location, time, and whether the music encounter was actively sought or occurred passively. Based on these results, we outline design implications for music information retrieval software, and suggest an extension of 'laid back' searching

Harmony and Technology Enhanced Learning

New technologies offer rich opportunities to support education in harmony. In this chapter we consider theoretical perspectives and underlying principles behind technologies for learning and teaching harmony. Such perspectives help in matching existing and future technologies to educational purposes, and to inspire the creative re-appropriation of technologies