Symbolic music generation includes various tasks for understanding human-composed or -performed music and mimicking the process for producing them. It particularly aims to computationally model real-world music using symbolic representations, such as Musical Instrument Digital Interface (MIDI). We are interested in several tasks that have been achieved increasing attention in the MIR field.
Automatic melody harmonization is a task to find coherent chords or an arrangement for the given melody. It has been important for understanding human composition by imitating the harmonizing process of the composers. It can also reduce a barrier to creating music without expertise.
In our lab, we mainly have focused on finding a chord label sequence for the given symbolic melody notes.
Automatic performance generation focuses on mimicking human behaviors for conveying music from the written score to the actual performance. One of the main objectives of this field is to reproduce the symbolic representations of the expressive attributes, including the loudness or timing of notes, from the given musical pieces.