The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …

Musical co-creativity aims at making humans and computers collaborate to compose music.
As an MIR team in computational musicology, we experimented with co-creativity when …

This paper has two different aims: presenting the problem of target-based computer-assisted
orchestration and introducing a new computational framework to solve it, called Orchidea …

The collaborative research and development project DYCI2, Creative Dynamics of
Improvised Interaction, focuses on conceiving, adapting, and bringing into play efficient …

We present a statistical-modeling method for piano reduction, ie converting an ensemble
score into piano scores, that can control performance difficulty. While previous studies have …

Music rearrangement is a common music practice of reconstructing and reconceptualizing a
piece using new composition or instrumentation styles, which is also an important task of …

Recently, the field of musical co-creativity has gained some momentum. In this context, our
goal is twofold: to develop an intelligent listening and predictive module of chord sequences …

This article introduces the Projective Orchestral Database (POD), a collection of MIDI scores
composed of pairs linking piano scores to their corresponding orchestrations. To the best of …

We study a method for converting the music style of a given melody to a target style (eg from
classical music style to pop music style) based on unsupervised statistical learning …

This paper describes a neural music arrangement method that converts a given band score
into a piano score with an elementary or advanced level. The major challenge of this task …